Text Generation
Transformers
Safetensors
qwen3_5
image-text-to-text
nvfp4
modelopt
fp4
dense
multimodal
gated-deltanet
hybrid
mtp
speculative-decoding
conversational
8-bit precision
Instructions to use vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt") model = AutoModelForMultimodalLM.from_pretrained("vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt
- SGLang
How to use vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt with Docker Model Runner:
docker model run hf.co/vroomfondel/Qwen3.8-27B-NVFP4-ModelOpt
Upload NVFP4 (ModelOpt) quantization
Browse files- .gitattributes +1 -0
- .quant_summary.txt +0 -0
- README.md +59 -0
- chat_template.jinja +170 -0
- config.json +473 -0
- generation_config.json +12 -0
- hf_quant_config.json +308 -0
- model-00001-of-00003.safetensors +3 -0
- model-00002-of-00003.safetensors +3 -0
- model-00003-of-00003.safetensors +3 -0
- model.safetensors.index.json +0 -0
- preprocessor_config.json +21 -0
- processor_config.json +60 -0
- tokenizer.json +3 -0
- tokenizer_config.json +305 -0
- video_preprocessor_config.json +21 -0
- vocab.json +0 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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.quant_summary.txt
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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: Qwen/Qwen3.8-27B
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base_model_relation: quantized
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pipeline_tag: text-generation
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tags:
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- modelopt
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- nvfp4
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- fp4
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---
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# qwen3.8-27b-nvfp4-modelopt
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NVFP4 quantization of [Qwen/Qwen3.8-27B](https://huggingface.co/Qwen/Qwen3.8-27B) via NVIDIA ModelOpt.
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<!-- BEGIN quant:preview -->
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## Quantization details (auto-generated)
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- **source model:** [Qwen/Qwen3.8-27B](https://huggingface.co/Qwen/Qwen3.8-27B)
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- **qformat:** `nvfp4` **kv_cache:** `fp8`
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- **calibration:** `?` samples from `?`
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- **producer:** NVIDIA ModelOpt `?`
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- **generated:** ?
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_Before/after sample generation was skipped for this run (`SKIP_GENERATE=1`)._
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<!-- END quant:preview -->
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<!-- BEGIN quant:remarks -->
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## Notes
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### Validation status -- structurally verified and smoke-tested coherent
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Quantized and served on a single DGX Spark (GB10/sm121) on 2026-08-15. The export passed every structural check: the vision tower is BF16 (333 tensors, zero scale tensors, dtypes and shapes identical to the source), `quant_algo` is `NVFP4` rather than `MIXED_PRECISION`, the FP8 KV scales sit on exactly the 16 full-attention layers (indices 3, 7, ..., 63), `in_proj_qkv` is NVFP4-packed on all 48 Gated-DeltaNet layers while `conv1d`/`in_proj_a`/`in_proj_b` stayed BF16, and all 15 `mtp.*` tensors are present and unquantized. Serving on SGLang 0.5.17 then produced coherent output on all four probe types (German two-sentence explanation, a multi-step train word problem, a five-sentence historical paragraph, a translation), each finishing with `finish_reason=stop`. The word problem was solved correctly (17:00, with the right derivation), which is the more informative signal: a broken Gated-DeltaNet path degrades into word salad rather than into arithmetic mistakes. This is a four-prompt smoke test, not an evaluation -- GSM8K or a comparable suite is still owed before any quality claim.
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### Uniform W4A4 on a Gated-DeltaNet hybrid
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Unlike NVIDIA's Qwen3.5/3.6 NVFP4 releases, which quantize the FFN/expert path and leave attention in BF16, this build quantizes attention as well, including the Gated-DeltaNet linear-attention path that carries 48 of the model's 64 layers. That is the deliberate point of the profile and it is also where the risk sits: an inadequately loaded scale on the fused `linear_attn.in_proj_qkv` degrades this architecture into complete word salad rather than into a measurable accuracy drop. Judge the build on generated output, not on the fact that it loads.
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### Serving requires the qwen3_5 attention-quant and KV-scale loader changes
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Because attention is quantized and FP8 KV scales are baked into the checkpoint, SGLang needs the `qwen3_5` attention-quant override and baked-KV-scale loader changes (sgl-project/sglang PR #31220) plus the NVFP4 scalar-scale fix for merged and fused linears (PR #29151, merged upstream 2026-07-13) that the fused Gated-DeltaNet `in_proj_qkv` depends on. Use the `flashinfer` attention backend: the `triton` backend hits a forward-time crash in `RadixLinearAttention.forward` for this exact configuration (sgl-project/sglang#29577, still open). A reliable check that the KV scales actually loaded is that the server logs "Using FP8 KV cache but no scaling factors provided" zero times.
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### Multimodal, vision tower kept BF16
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Calibration is text-only, so the 27-layer vision tower, its merger and the embeddings are excluded from quantization and stay BF16, avoiding the amax=0 degenerate-quant failure mode. The language-side FFNs that consume projected image tokens ARE quantized, and they were calibrated on text alone, so the image path is the least-validated surface of this build and should be checked against the BF16 source before being relied on.
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### BF16 MTP head, speculative decoding off by default
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The NEXTN/MTP draft head (`mtp_num_hidden_layers=1`) ships unquantized: transformers drops `mtp.*` at load for every Qwen3.5 architecture, so ModelOpt never sees it and passes the tensors through as BF16. Speculative decoding is therefore available but is left disabled in the shipped serving profile until bare serving is verified coherent, so that a quality regression can never be confused with a drafter problem.
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### Quantize on a single Spark with offload, not force-on-GPU
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Quantize with `SEQ_DEVICE_MAP=0` (offload / `device_map=auto`). GPU and CPU share the same ~121 GB unified memory pool on a DGX Spark, so offloading the 55.6 GB source costs nothing here. Do NOT use `SEQ_DEVICE_MAP=1` with a high `GPU_MAX_MEM_PCT` on a single Spark: that reserves most of the shared pool as GPU and OOM-kills weight loading regardless of the percentage. Force-on-GPU is a multi-GPU (4x H200) setting only.
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<!-- END quant:remarks -->
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chat_template.jinja
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{%- set image_count = namespace(value=0) %}
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{%- set video_count = namespace(value=0) %}
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| 3 |
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{%- macro render_content(content, do_vision_count, is_system_content=false) %}
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| 4 |
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{%- if content is string %}
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{{- content }}
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| 6 |
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{%- elif content is iterable and content is not mapping %}
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{%- for item in content %}
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| 8 |
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{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
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| 9 |
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{%- if is_system_content %}
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| 10 |
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{{- raise_exception('System message cannot contain images.') }}
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| 11 |
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{%- endif %}
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| 12 |
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{%- if do_vision_count %}
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| 13 |
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{%- set image_count.value = image_count.value + 1 %}
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{%- endif %}
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{%- if add_vision_id %}
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{{- 'Picture ' ~ image_count.value ~ ': ' }}
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{%- endif %}
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{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
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{%- elif 'video' in item or item.type == 'video' %}
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{%- if is_system_content %}
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{{- raise_exception('System message cannot contain videos.') }}
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| 22 |
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{%- endif %}
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{%- if do_vision_count %}
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{%- set video_count.value = video_count.value + 1 %}
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| 25 |
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{%- endif %}
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{%- if add_vision_id %}
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| 27 |
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{{- 'Video ' ~ video_count.value ~ ': ' }}
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{%- endif %}
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{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
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{%- elif 'text' in item %}
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{{- item.text }}
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{%- else %}
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| 33 |
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{{- raise_exception('Unexpected item type in content.') }}
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| 34 |
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{%- endif %}
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| 35 |
+
{%- endfor %}
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{%- elif content is none or content is undefined %}
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{{- '' }}
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{%- else %}
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| 39 |
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{{- raise_exception('Unexpected content type.') }}
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{%- endif %}
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| 41 |
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{%- endmacro %}
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{%- if not messages %}
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| 43 |
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{{- raise_exception('No messages provided.') }}
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| 44 |
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{%- endif %}
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| 45 |
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{%- set reasoning_instructions = '' %}
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| 46 |
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{%- if enable_thinking is undefined or enable_thinking is true %}
|
| 47 |
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{%- set resolved_reasoning_effort = reasoning_effort|default('xhigh') %}
|
| 48 |
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{%- if resolved_reasoning_effort not in ('xhigh', 'medium', 'low') %}
|
| 49 |
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{{- raise_exception('Unexpected reasoning effort ' ~ reasoning_effort ~ '. Supported types are xhigh (default), medium, and low.') }}
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| 50 |
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{%- endif %}
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| 51 |
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{%- if resolved_reasoning_effort == 'xhigh' %}
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| 52 |
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{%- set reasoning_instructions = 'Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.' %}
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| 53 |
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{%- elif resolved_reasoning_effort == 'low' %}
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| 54 |
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{%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}
|
| 55 |
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{%- endif %}
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| 56 |
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{%- endif %}
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| 57 |
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{%- if tools and tools is iterable and tools is not mapping %}
|
| 58 |
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{{- '<|im_start|>system\n' }}
|
| 59 |
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{%- if reasoning_instructions %}
|
| 60 |
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{{- reasoning_instructions + '\n\n' }}
|
| 61 |
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{%- endif %}
|
| 62 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 63 |
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{%- for tool in tools %}
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| 64 |
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{{- "\n" }}
|
| 65 |
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{{- tool | tojson }}
|
| 66 |
+
{%- endfor %}
|
| 67 |
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{{- "\n</tools>" }}
|
| 68 |
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{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 69 |
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{%- if messages[0].role == 'system' %}
|
| 70 |
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{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 71 |
+
{%- if content %}
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| 72 |
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{{- '\n\n' + content }}
|
| 73 |
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{%- endif %}
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| 74 |
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{%- endif %}
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| 75 |
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{{- '<|im_end|>\n' }}
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| 76 |
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{%- else %}
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| 77 |
+
{%- if messages[0].role == 'system' %}
|
| 78 |
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{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 79 |
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{%- if content %}
|
| 80 |
+
{{- '<|im_start|>system\n' + (reasoning_instructions + '\n\n' if reasoning_instructions else '') + content + '<|im_end|>\n' }}
|
| 81 |
+
{%- elif reasoning_instructions %}
|
| 82 |
+
{{- '<|im_start|>system\n' + reasoning_instructions + '<|im_end|>\n' }}
|
| 83 |
+
{%- endif %}
|
| 84 |
+
{%- elif reasoning_instructions %}
|
| 85 |
+
{{- '<|im_start|>system\n' + reasoning_instructions + '<|im_end|>\n' }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- endif %}
|
| 88 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 89 |
+
{%- for message in messages[::-1] %}
|
| 90 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 91 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 92 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 93 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 94 |
+
{%- set ns.multi_step_tool = false %}
|
| 95 |
+
{%- set ns.last_query_index = index %}
|
| 96 |
+
{%- endif %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endfor %}
|
| 99 |
+
{%- if ns.multi_step_tool %}
|
| 100 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 101 |
+
{%- endif %}
|
| 102 |
+
{%- for message in messages %}
|
| 103 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 104 |
+
{%- if message.role == "system" %}
|
| 105 |
+
{%- if not loop.first %}
|
| 106 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 107 |
+
{%- endif %}
|
| 108 |
+
{%- elif message.role == "user" %}
|
| 109 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 110 |
+
{%- elif message.role == "assistant" %}
|
| 111 |
+
{%- set reasoning_content = '' %}
|
| 112 |
+
{%- if message.reasoning_content is string %}
|
| 113 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 114 |
+
{%- endif %}
|
| 115 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 116 |
+
{%- if preserve_thinking is undefined or preserve_thinking is true or loop.index0 > ns.last_query_index %}
|
| 117 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 118 |
+
{%- else %}
|
| 119 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 120 |
+
{%- endif %}
|
| 121 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 122 |
+
{%- for tool_call in message.tool_calls %}
|
| 123 |
+
{%- if tool_call.function is defined %}
|
| 124 |
+
{%- set tool_call = tool_call.function %}
|
| 125 |
+
{%- endif %}
|
| 126 |
+
{%- if loop.first %}
|
| 127 |
+
{%- if content|trim %}
|
| 128 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 129 |
+
{%- else %}
|
| 130 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 131 |
+
{%- endif %}
|
| 132 |
+
{%- else %}
|
| 133 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{%- if tool_call.arguments is defined and tool_call.arguments != '' %}
|
| 136 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 137 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 138 |
+
{%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}
|
| 139 |
+
{{- args_value }}
|
| 140 |
+
{{- '\n</parameter>\n' }}
|
| 141 |
+
{%- endfor %}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{{- '</function>\n</tool_call>' }}
|
| 144 |
+
{%- endfor %}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{{- '<|im_end|>\n' }}
|
| 147 |
+
{%- elif message.role == "tool" %}
|
| 148 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 149 |
+
{{- '<|im_start|>user' }}
|
| 150 |
+
{%- endif %}
|
| 151 |
+
{{- '\n<tool_response>\n' }}
|
| 152 |
+
{{- content }}
|
| 153 |
+
{{- '\n</tool_response>' }}
|
| 154 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 155 |
+
{{- '<|im_end|>\n' }}
|
| 156 |
+
{%- elif loop.last %}
|
| 157 |
+
{{- '<|im_end|>\n' }}
|
| 158 |
+
{%- endif %}
|
| 159 |
+
{%- else %}
|
| 160 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 161 |
+
{%- endif %}
|
| 162 |
+
{%- endfor %}
|
| 163 |
+
{%- if add_generation_prompt %}
|
| 164 |
+
{{- '<|im_start|>assistant\n' }}
|
| 165 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 166 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 167 |
+
{%- else %}
|
| 168 |
+
{{- '<think>\n' }}
|
| 169 |
+
{%- endif %}
|
| 170 |
+
{%- endif %}
|
config.json
ADDED
|
@@ -0,0 +1,473 @@
|
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|
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|
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|
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|
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|
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|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"Qwen3_5ForConditionalGeneration"
|
| 4 |
+
],
|
| 5 |
+
"dtype": "bfloat16",
|
| 6 |
+
"image_token_id": 248056,
|
| 7 |
+
"language_model_only": false,
|
| 8 |
+
"model_type": "qwen3_5",
|
| 9 |
+
"text_config": {
|
| 10 |
+
"attention_bias": false,
|
| 11 |
+
"attention_dropout": 0.0,
|
| 12 |
+
"attn_output_gate": true,
|
| 13 |
+
"bos_token_id": 248044,
|
| 14 |
+
"dtype": "bfloat16",
|
| 15 |
+
"eos_token_id": 248044,
|
| 16 |
+
"full_attention_interval": 4,
|
| 17 |
+
"head_dim": 256,
|
| 18 |
+
"hidden_act": "silu",
|
| 19 |
+
"hidden_size": 5120,
|
| 20 |
+
"initializer_range": 0.02,
|
| 21 |
+
"intermediate_size": 17408,
|
| 22 |
+
"layer_types": [
|
| 23 |
+
"linear_attention",
|
| 24 |
+
"linear_attention",
|
| 25 |
+
"linear_attention",
|
| 26 |
+
"full_attention",
|
| 27 |
+
"linear_attention",
|
| 28 |
+
"linear_attention",
|
| 29 |
+
"linear_attention",
|
| 30 |
+
"full_attention",
|
| 31 |
+
"linear_attention",
|
| 32 |
+
"linear_attention",
|
| 33 |
+
"linear_attention",
|
| 34 |
+
"full_attention",
|
| 35 |
+
"linear_attention",
|
| 36 |
+
"linear_attention",
|
| 37 |
+
"linear_attention",
|
| 38 |
+
"full_attention",
|
| 39 |
+
"linear_attention",
|
| 40 |
+
"linear_attention",
|
| 41 |
+
"linear_attention",
|
| 42 |
+
"full_attention",
|
| 43 |
+
"linear_attention",
|
| 44 |
+
"linear_attention",
|
| 45 |
+
"linear_attention",
|
| 46 |
+
"full_attention",
|
| 47 |
+
"linear_attention",
|
| 48 |
+
"linear_attention",
|
| 49 |
+
"linear_attention",
|
| 50 |
+
"full_attention",
|
| 51 |
+
"linear_attention",
|
| 52 |
+
"linear_attention",
|
| 53 |
+
"linear_attention",
|
| 54 |
+
"full_attention",
|
| 55 |
+
"linear_attention",
|
| 56 |
+
"linear_attention",
|
| 57 |
+
"linear_attention",
|
| 58 |
+
"full_attention",
|
| 59 |
+
"linear_attention",
|
| 60 |
+
"linear_attention",
|
| 61 |
+
"linear_attention",
|
| 62 |
+
"full_attention",
|
| 63 |
+
"linear_attention",
|
| 64 |
+
"linear_attention",
|
| 65 |
+
"linear_attention",
|
| 66 |
+
"full_attention",
|
| 67 |
+
"linear_attention",
|
| 68 |
+
"linear_attention",
|
| 69 |
+
"linear_attention",
|
| 70 |
+
"full_attention",
|
| 71 |
+
"linear_attention",
|
| 72 |
+
"linear_attention",
|
| 73 |
+
"linear_attention",
|
| 74 |
+
"full_attention",
|
| 75 |
+
"linear_attention",
|
| 76 |
+
"linear_attention",
|
| 77 |
+
"linear_attention",
|
| 78 |
+
"full_attention",
|
| 79 |
+
"linear_attention",
|
| 80 |
+
"linear_attention",
|
| 81 |
+
"linear_attention",
|
| 82 |
+
"full_attention",
|
| 83 |
+
"linear_attention",
|
| 84 |
+
"linear_attention",
|
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"*layers.28.linear_attn.in_proj_b",
|
| 365 |
+
"*layers.29.linear_attn.conv1d",
|
| 366 |
+
"*layers.29.linear_attn.in_proj_a",
|
| 367 |
+
"*layers.29.linear_attn.in_proj_b",
|
| 368 |
+
"*layers.30.linear_attn.conv1d",
|
| 369 |
+
"*layers.30.linear_attn.in_proj_a",
|
| 370 |
+
"*layers.30.linear_attn.in_proj_b",
|
| 371 |
+
"*layers.32.linear_attn.conv1d",
|
| 372 |
+
"*layers.32.linear_attn.in_proj_a",
|
| 373 |
+
"*layers.32.linear_attn.in_proj_b",
|
| 374 |
+
"*layers.33.linear_attn.conv1d",
|
| 375 |
+
"*layers.33.linear_attn.in_proj_a",
|
| 376 |
+
"*layers.33.linear_attn.in_proj_b",
|
| 377 |
+
"*layers.34.linear_attn.conv1d",
|
| 378 |
+
"*layers.34.linear_attn.in_proj_a",
|
| 379 |
+
"*layers.34.linear_attn.in_proj_b",
|
| 380 |
+
"*layers.36.linear_attn.conv1d",
|
| 381 |
+
"*layers.36.linear_attn.in_proj_a",
|
| 382 |
+
"*layers.36.linear_attn.in_proj_b",
|
| 383 |
+
"*layers.37.linear_attn.conv1d",
|
| 384 |
+
"*layers.37.linear_attn.in_proj_a",
|
| 385 |
+
"*layers.37.linear_attn.in_proj_b",
|
| 386 |
+
"*layers.38.linear_attn.conv1d",
|
| 387 |
+
"*layers.38.linear_attn.in_proj_a",
|
| 388 |
+
"*layers.38.linear_attn.in_proj_b",
|
| 389 |
+
"*layers.4.linear_attn.conv1d",
|
| 390 |
+
"*layers.4.linear_attn.in_proj_a",
|
| 391 |
+
"*layers.4.linear_attn.in_proj_b",
|
| 392 |
+
"*layers.40.linear_attn.conv1d",
|
| 393 |
+
"*layers.40.linear_attn.in_proj_a",
|
| 394 |
+
"*layers.40.linear_attn.in_proj_b",
|
| 395 |
+
"*layers.41.linear_attn.conv1d",
|
| 396 |
+
"*layers.41.linear_attn.in_proj_a",
|
| 397 |
+
"*layers.41.linear_attn.in_proj_b",
|
| 398 |
+
"*layers.42.linear_attn.conv1d",
|
| 399 |
+
"*layers.42.linear_attn.in_proj_a",
|
| 400 |
+
"*layers.42.linear_attn.in_proj_b",
|
| 401 |
+
"*layers.44.linear_attn.conv1d",
|
| 402 |
+
"*layers.44.linear_attn.in_proj_a",
|
| 403 |
+
"*layers.44.linear_attn.in_proj_b",
|
| 404 |
+
"*layers.45.linear_attn.conv1d",
|
| 405 |
+
"*layers.45.linear_attn.in_proj_a",
|
| 406 |
+
"*layers.45.linear_attn.in_proj_b",
|
| 407 |
+
"*layers.46.linear_attn.conv1d",
|
| 408 |
+
"*layers.46.linear_attn.in_proj_a",
|
| 409 |
+
"*layers.46.linear_attn.in_proj_b",
|
| 410 |
+
"*layers.48.linear_attn.conv1d",
|
| 411 |
+
"*layers.48.linear_attn.in_proj_a",
|
| 412 |
+
"*layers.48.linear_attn.in_proj_b",
|
| 413 |
+
"*layers.49.linear_attn.conv1d",
|
| 414 |
+
"*layers.49.linear_attn.in_proj_a",
|
| 415 |
+
"*layers.49.linear_attn.in_proj_b",
|
| 416 |
+
"*layers.5.linear_attn.conv1d",
|
| 417 |
+
"*layers.5.linear_attn.in_proj_a",
|
| 418 |
+
"*layers.5.linear_attn.in_proj_b",
|
| 419 |
+
"*layers.50.linear_attn.conv1d",
|
| 420 |
+
"*layers.50.linear_attn.in_proj_a",
|
| 421 |
+
"*layers.50.linear_attn.in_proj_b",
|
| 422 |
+
"*layers.52.linear_attn.conv1d",
|
| 423 |
+
"*layers.52.linear_attn.in_proj_a",
|
| 424 |
+
"*layers.52.linear_attn.in_proj_b",
|
| 425 |
+
"*layers.53.linear_attn.conv1d",
|
| 426 |
+
"*layers.53.linear_attn.in_proj_a",
|
| 427 |
+
"*layers.53.linear_attn.in_proj_b",
|
| 428 |
+
"*layers.54.linear_attn.conv1d",
|
| 429 |
+
"*layers.54.linear_attn.in_proj_a",
|
| 430 |
+
"*layers.54.linear_attn.in_proj_b",
|
| 431 |
+
"*layers.56.linear_attn.conv1d",
|
| 432 |
+
"*layers.56.linear_attn.in_proj_a",
|
| 433 |
+
"*layers.56.linear_attn.in_proj_b",
|
| 434 |
+
"*layers.57.linear_attn.conv1d",
|
| 435 |
+
"*layers.57.linear_attn.in_proj_a",
|
| 436 |
+
"*layers.57.linear_attn.in_proj_b",
|
| 437 |
+
"*layers.58.linear_attn.conv1d",
|
| 438 |
+
"*layers.58.linear_attn.in_proj_a",
|
| 439 |
+
"*layers.58.linear_attn.in_proj_b",
|
| 440 |
+
"*layers.6.linear_attn.conv1d",
|
| 441 |
+
"*layers.6.linear_attn.in_proj_a",
|
| 442 |
+
"*layers.6.linear_attn.in_proj_b",
|
| 443 |
+
"*layers.60.linear_attn.conv1d",
|
| 444 |
+
"*layers.60.linear_attn.in_proj_a",
|
| 445 |
+
"*layers.60.linear_attn.in_proj_b",
|
| 446 |
+
"*layers.61.linear_attn.conv1d",
|
| 447 |
+
"*layers.61.linear_attn.in_proj_a",
|
| 448 |
+
"*layers.61.linear_attn.in_proj_b",
|
| 449 |
+
"*layers.62.linear_attn.conv1d",
|
| 450 |
+
"*layers.62.linear_attn.in_proj_a",
|
| 451 |
+
"*layers.62.linear_attn.in_proj_b",
|
| 452 |
+
"*layers.8.linear_attn.conv1d",
|
| 453 |
+
"*layers.8.linear_attn.in_proj_a",
|
| 454 |
+
"*layers.8.linear_attn.in_proj_b",
|
| 455 |
+
"*layers.9.linear_attn.conv1d",
|
| 456 |
+
"*layers.9.linear_attn.in_proj_a",
|
| 457 |
+
"*layers.9.linear_attn.in_proj_b",
|
| 458 |
+
"*visual*"
|
| 459 |
+
],
|
| 460 |
+
"quant_algo": "NVFP4",
|
| 461 |
+
"kv_cache_scheme": {
|
| 462 |
+
"dynamic": false,
|
| 463 |
+
"num_bits": 8,
|
| 464 |
+
"type": "float"
|
| 465 |
+
},
|
| 466 |
+
"producer": {
|
| 467 |
+
"name": "modelopt",
|
| 468 |
+
"version": "0.45.0"
|
| 469 |
+
},
|
| 470 |
+
"quant_method": "modelopt"
|
| 471 |
+
},
|
| 472 |
+
"torch_dtype": "bfloat16"
|
| 473 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token_id": 248044,
|
| 3 |
+
"do_sample": true,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
248046,
|
| 6 |
+
248044
|
| 7 |
+
],
|
| 8 |
+
"pad_token_id": 248044,
|
| 9 |
+
"temperature": 1.0,
|
| 10 |
+
"top_k": 20,
|
| 11 |
+
"top_p": 0.95
|
| 12 |
+
}
|
hf_quant_config.json
ADDED
|
@@ -0,0 +1,308 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
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|
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|
|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
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|
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|
|
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|
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|
|
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|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"producer": {
|
| 3 |
+
"name": "modelopt",
|
| 4 |
+
"version": "0.45.0"
|
| 5 |
+
},
|
| 6 |
+
"quantization": {
|
| 7 |
+
"quant_algo": "NVFP4",
|
| 8 |
+
"kv_cache_quant_algo": "FP8",
|
| 9 |
+
"group_size": 16,
|
| 10 |
+
"exclude_modules": [
|
| 11 |
+
"lm_head",
|
| 12 |
+
"model.language_model.embed_tokens",
|
| 13 |
+
"model.language_model.layers.0.linear_attn.conv1d",
|
| 14 |
+
"model.language_model.layers.0.linear_attn.in_proj_a",
|
| 15 |
+
"model.language_model.layers.0.linear_attn.in_proj_b",
|
| 16 |
+
"model.language_model.layers.1.linear_attn.conv1d",
|
| 17 |
+
"model.language_model.layers.1.linear_attn.in_proj_a",
|
| 18 |
+
"model.language_model.layers.1.linear_attn.in_proj_b",
|
| 19 |
+
"model.language_model.layers.10.linear_attn.conv1d",
|
| 20 |
+
"model.language_model.layers.10.linear_attn.in_proj_a",
|
| 21 |
+
"model.language_model.layers.10.linear_attn.in_proj_b",
|
| 22 |
+
"model.language_model.layers.12.linear_attn.conv1d",
|
| 23 |
+
"model.language_model.layers.12.linear_attn.in_proj_a",
|
| 24 |
+
"model.language_model.layers.12.linear_attn.in_proj_b",
|
| 25 |
+
"model.language_model.layers.13.linear_attn.conv1d",
|
| 26 |
+
"model.language_model.layers.13.linear_attn.in_proj_a",
|
| 27 |
+
"model.language_model.layers.13.linear_attn.in_proj_b",
|
| 28 |
+
"model.language_model.layers.14.linear_attn.conv1d",
|
| 29 |
+
"model.language_model.layers.14.linear_attn.in_proj_a",
|
| 30 |
+
"model.language_model.layers.14.linear_attn.in_proj_b",
|
| 31 |
+
"model.language_model.layers.16.linear_attn.conv1d",
|
| 32 |
+
"model.language_model.layers.16.linear_attn.in_proj_a",
|
| 33 |
+
"model.language_model.layers.16.linear_attn.in_proj_b",
|
| 34 |
+
"model.language_model.layers.17.linear_attn.conv1d",
|
| 35 |
+
"model.language_model.layers.17.linear_attn.in_proj_a",
|
| 36 |
+
"model.language_model.layers.17.linear_attn.in_proj_b",
|
| 37 |
+
"model.language_model.layers.18.linear_attn.conv1d",
|
| 38 |
+
"model.language_model.layers.18.linear_attn.in_proj_a",
|
| 39 |
+
"model.language_model.layers.18.linear_attn.in_proj_b",
|
| 40 |
+
"model.language_model.layers.2.linear_attn.conv1d",
|
| 41 |
+
"model.language_model.layers.2.linear_attn.in_proj_a",
|
| 42 |
+
"model.language_model.layers.2.linear_attn.in_proj_b",
|
| 43 |
+
"model.language_model.layers.20.linear_attn.conv1d",
|
| 44 |
+
"model.language_model.layers.20.linear_attn.in_proj_a",
|
| 45 |
+
"model.language_model.layers.20.linear_attn.in_proj_b",
|
| 46 |
+
"model.language_model.layers.21.linear_attn.conv1d",
|
| 47 |
+
"model.language_model.layers.21.linear_attn.in_proj_a",
|
| 48 |
+
"model.language_model.layers.21.linear_attn.in_proj_b",
|
| 49 |
+
"model.language_model.layers.22.linear_attn.conv1d",
|
| 50 |
+
"model.language_model.layers.22.linear_attn.in_proj_a",
|
| 51 |
+
"model.language_model.layers.22.linear_attn.in_proj_b",
|
| 52 |
+
"model.language_model.layers.24.linear_attn.conv1d",
|
| 53 |
+
"model.language_model.layers.24.linear_attn.in_proj_a",
|
| 54 |
+
"model.language_model.layers.24.linear_attn.in_proj_b",
|
| 55 |
+
"model.language_model.layers.25.linear_attn.conv1d",
|
| 56 |
+
"model.language_model.layers.25.linear_attn.in_proj_a",
|
| 57 |
+
"model.language_model.layers.25.linear_attn.in_proj_b",
|
| 58 |
+
"model.language_model.layers.26.linear_attn.conv1d",
|
| 59 |
+
"model.language_model.layers.26.linear_attn.in_proj_a",
|
| 60 |
+
"model.language_model.layers.26.linear_attn.in_proj_b",
|
| 61 |
+
"model.language_model.layers.28.linear_attn.conv1d",
|
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model-00001-of-00003.safetensors
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|
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|
preprocessor_config.json
ADDED
|
@@ -0,0 +1,21 @@
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|
|
|
|
|
|
|
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|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"size": {
|
| 3 |
+
"longest_edge": 16777216,
|
| 4 |
+
"shortest_edge": 65536
|
| 5 |
+
},
|
| 6 |
+
"patch_size": 16,
|
| 7 |
+
"temporal_patch_size": 2,
|
| 8 |
+
"merge_size": 2,
|
| 9 |
+
"image_mean": [
|
| 10 |
+
0.5,
|
| 11 |
+
0.5,
|
| 12 |
+
0.5
|
| 13 |
+
],
|
| 14 |
+
"image_std": [
|
| 15 |
+
0.5,
|
| 16 |
+
0.5,
|
| 17 |
+
0.5
|
| 18 |
+
],
|
| 19 |
+
"processor_class": "Qwen3VLProcessor",
|
| 20 |
+
"image_processor_type": "Qwen2VLImageProcessorFast"
|
| 21 |
+
}
|
processor_config.json
ADDED
|
@@ -0,0 +1,60 @@
|
|
|
|
|
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|
|
|
|
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|
|
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|
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|
|
|
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|
|
|
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|
|
|
|
| 1 |
+
{
|
| 2 |
+
"image_processor": {
|
| 3 |
+
"do_convert_rgb": true,
|
| 4 |
+
"do_normalize": true,
|
| 5 |
+
"do_rescale": true,
|
| 6 |
+
"do_resize": true,
|
| 7 |
+
"image_mean": [
|
| 8 |
+
0.5,
|
| 9 |
+
0.5,
|
| 10 |
+
0.5
|
| 11 |
+
],
|
| 12 |
+
"image_processor_type": "Qwen2VLImageProcessor",
|
| 13 |
+
"image_std": [
|
| 14 |
+
0.5,
|
| 15 |
+
0.5,
|
| 16 |
+
0.5
|
| 17 |
+
],
|
| 18 |
+
"merge_size": 2,
|
| 19 |
+
"patch_size": 16,
|
| 20 |
+
"resample": 3,
|
| 21 |
+
"rescale_factor": 0.00392156862745098,
|
| 22 |
+
"size": {
|
| 23 |
+
"longest_edge": 16777216,
|
| 24 |
+
"shortest_edge": 65536
|
| 25 |
+
},
|
| 26 |
+
"temporal_patch_size": 2
|
| 27 |
+
},
|
| 28 |
+
"processor_class": "Qwen3VLProcessor",
|
| 29 |
+
"video_processor": {
|
| 30 |
+
"do_convert_rgb": true,
|
| 31 |
+
"do_normalize": true,
|
| 32 |
+
"do_rescale": true,
|
| 33 |
+
"do_resize": true,
|
| 34 |
+
"do_sample_frames": true,
|
| 35 |
+
"fps": 2,
|
| 36 |
+
"image_mean": [
|
| 37 |
+
0.5,
|
| 38 |
+
0.5,
|
| 39 |
+
0.5
|
| 40 |
+
],
|
| 41 |
+
"image_std": [
|
| 42 |
+
0.5,
|
| 43 |
+
0.5,
|
| 44 |
+
0.5
|
| 45 |
+
],
|
| 46 |
+
"max_frames": 768,
|
| 47 |
+
"merge_size": 2,
|
| 48 |
+
"min_frames": 4,
|
| 49 |
+
"patch_size": 16,
|
| 50 |
+
"resample": 3,
|
| 51 |
+
"rescale_factor": 0.00392156862745098,
|
| 52 |
+
"return_metadata": false,
|
| 53 |
+
"size": {
|
| 54 |
+
"longest_edge": 25165824,
|
| 55 |
+
"shortest_edge": 4096
|
| 56 |
+
},
|
| 57 |
+
"temporal_patch_size": 2,
|
| 58 |
+
"video_processor_type": "Qwen3VLVideoProcessor"
|
| 59 |
+
}
|
| 60 |
+
}
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0997f410c57a1f4e53b09e4be8f4a172d90edd9564368fb0847030937229b9f3
|
| 3 |
+
size 12809320
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,305 @@
|
|
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|
|
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|
|
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|
|
|
|
|
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|
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|
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|
|
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|
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|
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|
|
|
|
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|
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|
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|
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|
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|
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|
|
|
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|
|
|
|
|
|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
|
|
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|
|
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|
|
|
|
|
|
|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"added_tokens_decoder": {
|
| 4 |
+
"248044": {
|
| 5 |
+
"content": "<|endoftext|>",
|
| 6 |
+
"lstrip": false,
|
| 7 |
+
"normalized": false,
|
| 8 |
+
"rstrip": false,
|
| 9 |
+
"single_word": false,
|
| 10 |
+
"special": true
|
| 11 |
+
},
|
| 12 |
+
"248045": {
|
| 13 |
+
"content": "<|im_start|>",
|
| 14 |
+
"lstrip": false,
|
| 15 |
+
"normalized": false,
|
| 16 |
+
"rstrip": false,
|
| 17 |
+
"single_word": false,
|
| 18 |
+
"special": true
|
| 19 |
+
},
|
| 20 |
+
"248046": {
|
| 21 |
+
"content": "<|im_end|>",
|
| 22 |
+
"lstrip": false,
|
| 23 |
+
"normalized": false,
|
| 24 |
+
"rstrip": false,
|
| 25 |
+
"single_word": false,
|
| 26 |
+
"special": true
|
| 27 |
+
},
|
| 28 |
+
"248047": {
|
| 29 |
+
"content": "<|object_ref_start|>",
|
| 30 |
+
"lstrip": false,
|
| 31 |
+
"normalized": false,
|
| 32 |
+
"rstrip": false,
|
| 33 |
+
"single_word": false,
|
| 34 |
+
"special": true
|
| 35 |
+
},
|
| 36 |
+
"248048": {
|
| 37 |
+
"content": "<|object_ref_end|>",
|
| 38 |
+
"lstrip": false,
|
| 39 |
+
"normalized": false,
|
| 40 |
+
"rstrip": false,
|
| 41 |
+
"single_word": false,
|
| 42 |
+
"special": true
|
| 43 |
+
},
|
| 44 |
+
"248049": {
|
| 45 |
+
"content": "<|box_start|>",
|
| 46 |
+
"lstrip": false,
|
| 47 |
+
"normalized": false,
|
| 48 |
+
"rstrip": false,
|
| 49 |
+
"single_word": false,
|
| 50 |
+
"special": true
|
| 51 |
+
},
|
| 52 |
+
"248050": {
|
| 53 |
+
"content": "<|box_end|>",
|
| 54 |
+
"lstrip": false,
|
| 55 |
+
"normalized": false,
|
| 56 |
+
"rstrip": false,
|
| 57 |
+
"single_word": false,
|
| 58 |
+
"special": true
|
| 59 |
+
},
|
| 60 |
+
"248051": {
|
| 61 |
+
"content": "<|quad_start|>",
|
| 62 |
+
"lstrip": false,
|
| 63 |
+
"normalized": false,
|
| 64 |
+
"rstrip": false,
|
| 65 |
+
"single_word": false,
|
| 66 |
+
"special": true
|
| 67 |
+
},
|
| 68 |
+
"248052": {
|
| 69 |
+
"content": "<|quad_end|>",
|
| 70 |
+
"lstrip": false,
|
| 71 |
+
"normalized": false,
|
| 72 |
+
"rstrip": false,
|
| 73 |
+
"single_word": false,
|
| 74 |
+
"special": true
|
| 75 |
+
},
|
| 76 |
+
"248053": {
|
| 77 |
+
"content": "<|vision_start|>",
|
| 78 |
+
"lstrip": false,
|
| 79 |
+
"normalized": false,
|
| 80 |
+
"rstrip": false,
|
| 81 |
+
"single_word": false,
|
| 82 |
+
"special": true
|
| 83 |
+
},
|
| 84 |
+
"248054": {
|
| 85 |
+
"content": "<|vision_end|>",
|
| 86 |
+
"lstrip": false,
|
| 87 |
+
"normalized": false,
|
| 88 |
+
"rstrip": false,
|
| 89 |
+
"single_word": false,
|
| 90 |
+
"special": true
|
| 91 |
+
},
|
| 92 |
+
"248055": {
|
| 93 |
+
"content": "<|vision_pad|>",
|
| 94 |
+
"lstrip": false,
|
| 95 |
+
"normalized": false,
|
| 96 |
+
"rstrip": false,
|
| 97 |
+
"single_word": false,
|
| 98 |
+
"special": true
|
| 99 |
+
},
|
| 100 |
+
"248056": {
|
| 101 |
+
"content": "<|image_pad|>",
|
| 102 |
+
"lstrip": false,
|
| 103 |
+
"normalized": false,
|
| 104 |
+
"rstrip": false,
|
| 105 |
+
"single_word": false,
|
| 106 |
+
"special": true
|
| 107 |
+
},
|
| 108 |
+
"248057": {
|
| 109 |
+
"content": "<|video_pad|>",
|
| 110 |
+
"lstrip": false,
|
| 111 |
+
"normalized": false,
|
| 112 |
+
"rstrip": false,
|
| 113 |
+
"single_word": false,
|
| 114 |
+
"special": true
|
| 115 |
+
},
|
| 116 |
+
"248058": {
|
| 117 |
+
"content": "<tool_call>",
|
| 118 |
+
"lstrip": false,
|
| 119 |
+
"normalized": false,
|
| 120 |
+
"rstrip": false,
|
| 121 |
+
"single_word": false,
|
| 122 |
+
"special": false
|
| 123 |
+
},
|
| 124 |
+
"248059": {
|
| 125 |
+
"content": "</tool_call>",
|
| 126 |
+
"lstrip": false,
|
| 127 |
+
"normalized": false,
|
| 128 |
+
"rstrip": false,
|
| 129 |
+
"single_word": false,
|
| 130 |
+
"special": false
|
| 131 |
+
},
|
| 132 |
+
"248060": {
|
| 133 |
+
"content": "<|fim_prefix|>",
|
| 134 |
+
"lstrip": false,
|
| 135 |
+
"normalized": false,
|
| 136 |
+
"rstrip": false,
|
| 137 |
+
"single_word": false,
|
| 138 |
+
"special": false
|
| 139 |
+
},
|
| 140 |
+
"248061": {
|
| 141 |
+
"content": "<|fim_middle|>",
|
| 142 |
+
"lstrip": false,
|
| 143 |
+
"normalized": false,
|
| 144 |
+
"rstrip": false,
|
| 145 |
+
"single_word": false,
|
| 146 |
+
"special": false
|
| 147 |
+
},
|
| 148 |
+
"248062": {
|
| 149 |
+
"content": "<|fim_suffix|>",
|
| 150 |
+
"lstrip": false,
|
| 151 |
+
"normalized": false,
|
| 152 |
+
"rstrip": false,
|
| 153 |
+
"single_word": false,
|
| 154 |
+
"special": false
|
| 155 |
+
},
|
| 156 |
+
"248063": {
|
| 157 |
+
"content": "<|fim_pad|>",
|
| 158 |
+
"lstrip": false,
|
| 159 |
+
"normalized": false,
|
| 160 |
+
"rstrip": false,
|
| 161 |
+
"single_word": false,
|
| 162 |
+
"special": false
|
| 163 |
+
},
|
| 164 |
+
"248064": {
|
| 165 |
+
"content": "<|repo_name|>",
|
| 166 |
+
"lstrip": false,
|
| 167 |
+
"normalized": false,
|
| 168 |
+
"rstrip": false,
|
| 169 |
+
"single_word": false,
|
| 170 |
+
"special": false
|
| 171 |
+
},
|
| 172 |
+
"248065": {
|
| 173 |
+
"content": "<|file_sep|>",
|
| 174 |
+
"lstrip": false,
|
| 175 |
+
"normalized": false,
|
| 176 |
+
"rstrip": false,
|
| 177 |
+
"single_word": false,
|
| 178 |
+
"special": false
|
| 179 |
+
},
|
| 180 |
+
"248066": {
|
| 181 |
+
"content": "<tool_response>",
|
| 182 |
+
"lstrip": false,
|
| 183 |
+
"normalized": false,
|
| 184 |
+
"rstrip": false,
|
| 185 |
+
"single_word": false,
|
| 186 |
+
"special": false
|
| 187 |
+
},
|
| 188 |
+
"248067": {
|
| 189 |
+
"content": "</tool_response>",
|
| 190 |
+
"lstrip": false,
|
| 191 |
+
"normalized": false,
|
| 192 |
+
"rstrip": false,
|
| 193 |
+
"single_word": false,
|
| 194 |
+
"special": false
|
| 195 |
+
},
|
| 196 |
+
"248068": {
|
| 197 |
+
"content": "<think>",
|
| 198 |
+
"lstrip": false,
|
| 199 |
+
"normalized": false,
|
| 200 |
+
"rstrip": false,
|
| 201 |
+
"single_word": false,
|
| 202 |
+
"special": false
|
| 203 |
+
},
|
| 204 |
+
"248069": {
|
| 205 |
+
"content": "</think>",
|
| 206 |
+
"lstrip": false,
|
| 207 |
+
"normalized": false,
|
| 208 |
+
"rstrip": false,
|
| 209 |
+
"single_word": false,
|
| 210 |
+
"special": false
|
| 211 |
+
},
|
| 212 |
+
"248070": {
|
| 213 |
+
"content": "<|audio_start|>",
|
| 214 |
+
"lstrip": false,
|
| 215 |
+
"normalized": false,
|
| 216 |
+
"rstrip": false,
|
| 217 |
+
"single_word": false,
|
| 218 |
+
"special": true
|
| 219 |
+
},
|
| 220 |
+
"248071": {
|
| 221 |
+
"content": "<|audio_end|>",
|
| 222 |
+
"lstrip": false,
|
| 223 |
+
"normalized": false,
|
| 224 |
+
"rstrip": false,
|
| 225 |
+
"single_word": false,
|
| 226 |
+
"special": true
|
| 227 |
+
},
|
| 228 |
+
"248072": {
|
| 229 |
+
"content": "<tts_pad>",
|
| 230 |
+
"lstrip": false,
|
| 231 |
+
"normalized": false,
|
| 232 |
+
"rstrip": false,
|
| 233 |
+
"single_word": false,
|
| 234 |
+
"special": true
|
| 235 |
+
},
|
| 236 |
+
"248073": {
|
| 237 |
+
"content": "<tts_text_bos>",
|
| 238 |
+
"lstrip": false,
|
| 239 |
+
"normalized": false,
|
| 240 |
+
"rstrip": false,
|
| 241 |
+
"single_word": false,
|
| 242 |
+
"special": true
|
| 243 |
+
},
|
| 244 |
+
"248074": {
|
| 245 |
+
"content": "<tts_text_eod>",
|
| 246 |
+
"lstrip": false,
|
| 247 |
+
"normalized": false,
|
| 248 |
+
"rstrip": false,
|
| 249 |
+
"single_word": false,
|
| 250 |
+
"special": true
|
| 251 |
+
},
|
| 252 |
+
"248075": {
|
| 253 |
+
"content": "<tts_text_bos_single>",
|
| 254 |
+
"lstrip": false,
|
| 255 |
+
"normalized": false,
|
| 256 |
+
"rstrip": false,
|
| 257 |
+
"single_word": false,
|
| 258 |
+
"special": true
|
| 259 |
+
},
|
| 260 |
+
"248076": {
|
| 261 |
+
"content": "<|audio_pad|>",
|
| 262 |
+
"lstrip": false,
|
| 263 |
+
"normalized": false,
|
| 264 |
+
"rstrip": false,
|
| 265 |
+
"single_word": false,
|
| 266 |
+
"special": true
|
| 267 |
+
}
|
| 268 |
+
},
|
| 269 |
+
"additional_special_tokens": [
|
| 270 |
+
"<|im_start|>",
|
| 271 |
+
"<|im_end|>",
|
| 272 |
+
"<|object_ref_start|>",
|
| 273 |
+
"<|object_ref_end|>",
|
| 274 |
+
"<|box_start|>",
|
| 275 |
+
"<|box_end|>",
|
| 276 |
+
"<|quad_start|>",
|
| 277 |
+
"<|quad_end|>",
|
| 278 |
+
"<|vision_start|>",
|
| 279 |
+
"<|vision_end|>",
|
| 280 |
+
"<|vision_pad|>",
|
| 281 |
+
"<|image_pad|>",
|
| 282 |
+
"<|video_pad|>"
|
| 283 |
+
],
|
| 284 |
+
"bos_token": null,
|
| 285 |
+
"chat_template": "{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- macro render_content(content, do_vision_count, is_system_content=false) %}\n {%- if content is string %}\n {{- content }}\n {%- elif content is iterable and content is not mapping %}\n {%- for item in content %}\n {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}\n {%- if is_system_content %}\n {{- raise_exception('System message cannot contain images.') }}\n {%- endif %}\n {%- if do_vision_count %}\n {%- set image_count.value = image_count.value + 1 %}\n {%- endif %}\n {%- if add_vision_id %}\n {{- 'Picture ' ~ image_count.value ~ ': ' }}\n {%- endif %}\n {{- '<|vision_start|><|image_pad|><|vision_end|>' }}\n {%- elif 'video' in item or item.type == 'video' %}\n {%- if is_system_content %}\n {{- raise_exception('System message cannot contain videos.') }}\n {%- endif %}\n {%- if do_vision_count %}\n {%- set video_count.value = video_count.value + 1 %}\n {%- endif %}\n {%- if add_vision_id %}\n {{- 'Video ' ~ video_count.value ~ ': ' }}\n {%- endif %}\n {{- '<|vision_start|><|video_pad|><|vision_end|>' }}\n {%- elif 'text' in item %}\n {{- item.text }}\n {%- else %}\n {{- raise_exception('Unexpected item type in content.') }}\n {%- endif %}\n {%- endfor %}\n {%- elif content is none or content is undefined %}\n {{- '' }}\n {%- else %}\n {{- raise_exception('Unexpected content type.') }}\n {%- endif %}\n{%- endmacro %}\n{%- if not messages %}\n {{- raise_exception('No messages provided.') }}\n{%- endif %}\n{%- set reasoning_instructions = '' %}\n{%- if enable_thinking is undefined or enable_thinking is true %}\n {%- set resolved_reasoning_effort = reasoning_effort|default('xhigh') %}\n {%- if resolved_reasoning_effort not in ('xhigh', 'medium', 'low') %}\n {{- raise_exception('Unexpected reasoning effort ' ~ reasoning_effort ~ '. Supported types are xhigh (default), medium, and low.') }}\n {%- endif %}\n {%- if resolved_reasoning_effort == 'xhigh' %}\n {%- set reasoning_instructions = 'Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.' %}\n {%- elif resolved_reasoning_effort == 'low' %}\n {%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}\n {%- endif %}\n{%- endif %}\n{%- if tools and tools is iterable and tools is not mapping %}\n {{- '<|im_start|>system\\n' }}\n {%- if reasoning_instructions %}\n {{- reasoning_instructions + '\\n\\n' }}\n {%- endif %}\n {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\" }}\n {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n {%- if messages[0].role == 'system' %}\n {%- set content = render_content(messages[0].content, false, true)|trim %}\n {%- if content %}\n {{- '\\n\\n' + content }}\n {%- endif %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {%- set content = render_content(messages[0].content, false, true)|trim %}\n {%- if content %}\n {{- '<|im_start|>system\\n' + (reasoning_instructions + '\\n\\n' if reasoning_instructions else '') + content + '<|im_end|>\\n' }}\n {%- elif reasoning_instructions %}\n {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n {%- endif %}\n {%- elif reasoning_instructions %}\n {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n {%- set index = (messages|length - 1) - loop.index0 %}\n {%- if ns.multi_step_tool and message.role == \"user\" %}\n {%- set content = render_content(message.content, false)|trim %}\n {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if ns.multi_step_tool %}\n {{- raise_exception('No user query found in messages.') }}\n{%- endif %}\n{%- for message in messages %}\n {%- set content = render_content(message.content, true)|trim %}\n {%- if message.role == \"system\" %}\n {%- if not loop.first %}\n {{- raise_exception('System message must be at the beginning.') }}\n {%- endif %}\n {%- elif message.role == \"user\" %}\n {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is string %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- endif %}\n {%- set reasoning_content = reasoning_content|trim %}\n {%- if preserve_thinking is undefined or preserve_thinking is true or loop.index0 > ns.last_query_index %}\n {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content + '\\n</think>\\n\\n' + content }}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {%- if loop.first %}\n {%- if content|trim %}\n {{- '\\n\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n {%- else %}\n {{- '<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n {%- endif %}\n {%- else %}\n {{- '\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n {%- endif %}\n {%- if tool_call.arguments is defined and tool_call.arguments != '' %}\n {%- for args_name, args_value in tool_call.arguments|items %}\n {{- '<parameter=' + args_name + '>\\n' }}\n {%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}\n {{- args_value }}\n {{- '\\n</parameter>\\n' }}\n {%- endfor %}\n {%- endif %}\n {{- '</function>\\n</tool_call>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- content }}\n {{- '\\n</tool_response>' }}\n {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n {{- '<|im_end|>\\n' }}\n {%- elif loop.last %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- else %}\n {{- raise_exception('Unexpected message role.') }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n {%- if enable_thinking is defined and enable_thinking is false %}\n {{- '<think>\\n\\n</think>\\n\\n' }}\n {%- else %}\n {{- '<think>\\n' }}\n {%- endif %}\n{%- endif %}",
|
| 286 |
+
"clean_up_tokenization_spaces": false,
|
| 287 |
+
"eos_token": "<|im_end|>",
|
| 288 |
+
"errors": "replace",
|
| 289 |
+
"model_max_length": 262144,
|
| 290 |
+
"pad_token": "<|endoftext|>",
|
| 291 |
+
"split_special_tokens": false,
|
| 292 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 293 |
+
"unk_token": null,
|
| 294 |
+
"add_bos_token": false,
|
| 295 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 296 |
+
"extra_special_tokens": {
|
| 297 |
+
"audio_bos_token": "<|audio_start|>",
|
| 298 |
+
"audio_eos_token": "<|audio_end|>",
|
| 299 |
+
"audio_token": "<|audio_pad|>",
|
| 300 |
+
"image_token": "<|image_pad|>",
|
| 301 |
+
"video_token": "<|video_pad|>",
|
| 302 |
+
"vision_bos_token": "<|vision_start|>",
|
| 303 |
+
"vision_eos_token": "<|vision_end|>"
|
| 304 |
+
}
|
| 305 |
+
}
|
video_preprocessor_config.json
ADDED
|
@@ -0,0 +1,21 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"size": {
|
| 3 |
+
"longest_edge": 25165824,
|
| 4 |
+
"shortest_edge": 4096
|
| 5 |
+
},
|
| 6 |
+
"patch_size": 16,
|
| 7 |
+
"temporal_patch_size": 2,
|
| 8 |
+
"merge_size": 2,
|
| 9 |
+
"image_mean": [
|
| 10 |
+
0.5,
|
| 11 |
+
0.5,
|
| 12 |
+
0.5
|
| 13 |
+
],
|
| 14 |
+
"image_std": [
|
| 15 |
+
0.5,
|
| 16 |
+
0.5,
|
| 17 |
+
0.5
|
| 18 |
+
],
|
| 19 |
+
"processor_class": "Qwen3VLProcessor",
|
| 20 |
+
"video_processor_type": "Qwen3VLVideoProcessor"
|
| 21 |
+
}
|
vocab.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|