Image-Text-to-Text
MLX
Safetensors
English
qwen3_5_moe
quantized
apple-silicon
Mixture of Experts
vision
hybrid-attention
gated-deltanet
turboquant
jangtq
jangtq2
agent
computer-use
gui-agents
conversational
Instructions to use JANGQ-AI/Holo3-35B-A3B-JANGTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use JANGQ-AI/Holo3-35B-A3B-JANGTQ with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("JANGQ-AI/Holo3-35B-A3B-JANGTQ") config = load_config("JANGQ-AI/Holo3-35B-A3B-JANGTQ") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use JANGQ-AI/Holo3-35B-A3B-JANGTQ with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "JANGQ-AI/Holo3-35B-A3B-JANGTQ"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "JANGQ-AI/Holo3-35B-A3B-JANGTQ" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent
How to use JANGQ-AI/Holo3-35B-A3B-JANGTQ with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "JANGQ-AI/Holo3-35B-A3B-JANGTQ"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default JANGQ-AI/Holo3-35B-A3B-JANGTQ
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use JANGQ-AI/Holo3-35B-A3B-JANGTQ with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "JANGQ-AI/Holo3-35B-A3B-JANGTQ"
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "JANGQ-AI/Holo3-35B-A3B-JANGTQ" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Add Holo3-35B-A3B JANGTQ2 (MLX) + VL tower + README
Browse files- .gitattributes +1 -0
- README.md +207 -0
- chat_template.jinja +154 -0
- config.json +129 -0
- generation_config.json +13 -0
- jang_config.json +34 -0
- jangtq_runtime.safetensors +3 -0
- merges.txt +0 -0
- model-00001-of-00012.safetensors +3 -0
- model-00002-of-00012.safetensors +3 -0
- model-00003-of-00012.safetensors +3 -0
- model-00004-of-00012.safetensors +3 -0
- model-00005-of-00012.safetensors +3 -0
- model-00006-of-00012.safetensors +3 -0
- model-00007-of-00012.safetensors +3 -0
- model-00008-of-00012.safetensors +3 -0
- model-00009-of-00012.safetensors +3 -0
- model-00010-of-00012.safetensors +3 -0
- model-00011-of-00012.safetensors +3 -0
- model-00012-of-00012.safetensors +3 -0
- model.safetensors.index.json +0 -0
- osaurus-x-banner.png +0 -0
- preprocessor_config.json +21 -0
- tokenizer.json +3 -0
- tokenizer_config.json +305 -0
- video_preprocessor_config.json +21 -0
- vocab.json +0 -0
.gitattributes
CHANGED
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst 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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README.md
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|
| 1 |
+
---
|
| 2 |
+
language:
|
| 3 |
+
- en
|
| 4 |
+
library_name: mlx
|
| 5 |
+
license: apache-2.0
|
| 6 |
+
pipeline_tag: image-text-to-text
|
| 7 |
+
base_model: Hcompany/Holo3-35B-A3B
|
| 8 |
+
tags:
|
| 9 |
+
- quantized
|
| 10 |
+
- apple-silicon
|
| 11 |
+
- mlx
|
| 12 |
+
- qwen3_5_moe
|
| 13 |
+
- moe
|
| 14 |
+
- vision
|
| 15 |
+
- hybrid-attention
|
| 16 |
+
- gated-deltanet
|
| 17 |
+
- turboquant
|
| 18 |
+
- jangtq
|
| 19 |
+
- jangtq2
|
| 20 |
+
- agent
|
| 21 |
+
- computer-use
|
| 22 |
+
- gui-agents
|
| 23 |
+
---
|
| 24 |
+
|
| 25 |
+
<p align="center">
|
| 26 |
+
<a href="https://osaurus.ai"><img src="./osaurus-x-banner.png" alt="Osaurus AI"></a>
|
| 27 |
+
</p>
|
| 28 |
+
|
| 29 |
+
<h3 align="center">Holo3 35B-A3B — JANGTQ2 (MLX)</h3>
|
| 30 |
+
<p align="center">TurboQuant codebook quantization of H Company's Holo3 GUI-agent VLM — routed experts at 2-bit via Lloyd-Max codebooks + Hadamard rotation, attention / embed / shared-expert / lm_head at 8-bit affine, vision tower preserved.</p>
|
| 31 |
+
|
| 32 |
+
<p align="center">
|
| 33 |
+
<a href="https://osaurus.ai"><img src="https://img.shields.io/badge/Web-osaurus.ai-blue" alt="Website"></a>
|
| 34 |
+
<a href="https://huggingface.co/JANGQ-AI"><img src="https://img.shields.io/badge/HF-JANGQ--AI-yellow?logo=huggingface" alt="JANGQ-AI"></a>
|
| 35 |
+
<a href="https://huggingface.co/Hcompany/Holo3-35B-A3B"><img src="https://img.shields.io/badge/Base-Holo3--35B--A3B-orange?logo=huggingface" alt="Holo3"></a>
|
| 36 |
+
</p>
|
| 37 |
+
|
| 38 |
+
---
|
| 39 |
+
|
| 40 |
+
## Model Details
|
| 41 |
+
|
| 42 |
+
| Property | Value |
|
| 43 |
+
|---|---|
|
| 44 |
+
| **Base model** | [`Hcompany/Holo3-35B-A3B`](https://huggingface.co/Hcompany/Holo3-35B-A3B) (finetune of `Qwen/Qwen3.5-35B-A3B`) |
|
| 45 |
+
| **Parameters (source)** | 35 B total, ~3 B active per token |
|
| 46 |
+
| **Architecture** | `qwen3_5_moe` — 40 decoder layers: 30 `Gated DeltaNet` (linear attn) + 10 full attention, 256 routed experts + 1 always-on shared expert |
|
| 47 |
+
| **Quantization format** | `weight_format: mxtq` — routed experts via TurboQuant codebook (2-bit), everything else affine 8-bit or fp16 passthrough |
|
| 48 |
+
| **Routed-expert storage** | `.tq_packed` (uint32) + `.tq_norms` (fp16) + `.tq_bits` (uint8); codebook + Hadamard signs re-derived deterministically at load |
|
| 49 |
+
| **Package size on disk** | **11.63 GB** across 12 shards |
|
| 50 |
+
| **Shipped tensors** | 1,930 total (1,597 language-model + 333 vision tower + 120 routed-expert TQ triples) |
|
| 51 |
+
| **Vocab** | 248,320 |
|
| 52 |
+
| **Context (position embeddings)** | 262,144 native |
|
| 53 |
+
| **Vision tower** | 27-layer ViT (hidden 1152, patch 16), preserved in fp16 |
|
| 54 |
+
| **Chat format** | Qwen `im_start`/`im_end` with `<think>` reasoning toggle; Holo3 XML tool-call grammar |
|
| 55 |
+
| **Use case** | GUI / computer-use agent (desktop, web, mobile) — designed for screenshot → action loops |
|
| 56 |
+
|
| 57 |
+
### Quantization details, per tensor category
|
| 58 |
+
|
| 59 |
+
| Category | Bits | Group / codebook | Notes |
|
| 60 |
+
|---|---|---|---|
|
| 61 |
+
| **Routed-expert MLP** (`mlp.switch_mlp.gate_proj`, `up_proj`, `down_proj`) | **2 (JANGTQ)** | 2² Lloyd-Max centroids + Hadamard rotation | `.tq_packed` + `.tq_norms` + `.tq_bits` triples |
|
| 62 |
+
| Embedding (`embed_tokens`), `lm_head` | 8 (affine) | group 64 | MLX-native `QuantizedLinear` |
|
| 63 |
+
| Full-attention projections (`q_proj`, `k_proj`, `v_proj`, `o_proj`) | 8 (affine) | group 64 | Gate-doubled q_proj for `attn_output_gate` |
|
| 64 |
+
| Linear-attention projections (`in_proj_qkv`, `in_proj_z`, `in_proj_b`, `in_proj_a`, `out_proj`) | 8 (affine) | group 64 | Gated DeltaNet |
|
| 65 |
+
| Shared-expert MLP (`gate_proj`, `up_proj`, `down_proj`) | 8 (affine) | group 64 | Always active per token |
|
| 66 |
+
| Router (`mlp.gate`) | fp16 passthrough | — | Precision-critical |
|
| 67 |
+
| Shared-expert gate (`shared_expert_gate`) | fp16 passthrough | — | sigmoid scalar gate |
|
| 68 |
+
| Norms (`*_layernorm`, `*_norm`), `A_log`, `dt_bias`, `conv1d` | fp16 passthrough | — | Un-quantized |
|
| 69 |
+
| Vision tower (333 tensors) | fp16 passthrough | — | `patch_embed.proj` axes pre-transposed to MLX layout |
|
| 70 |
+
|
| 71 |
+
JANGTQ ("TurboQuant") stores routed-expert weights as indices into a small Lloyd-Max codebook with a per-row norm, after a randomized Hadamard rotation that concentrates the distribution so quantization error is uniform. At inference, the input is rotated once per layer (cheap fused Metal kernel) and dot products happen against the codebook centroids directly, so we never dequantize back to affine. Compared to affine 2-bit at the same bit budget, this gives better quality **and** faster decode on the routed-expert MLP path.
|
| 72 |
+
|
| 73 |
+
---
|
| 74 |
+
|
| 75 |
+
## Usage
|
| 76 |
+
|
| 77 |
+
**JANGTQ requires our custom loader** — stock `mlx_lm.load()` can't parse `.tq_packed` tensors. You need `jang-tools` (free, public): <https://github.com/jjang-ai/jangq>.
|
| 78 |
+
|
| 79 |
+
```bash
|
| 80 |
+
pip install mlx mlx-lm mlx-vlm
|
| 81 |
+
git clone https://github.com/jjang-ai/jangq && pip install -e ./jangq/jang-tools
|
| 82 |
+
```
|
| 83 |
+
|
| 84 |
+
### Text
|
| 85 |
+
|
| 86 |
+
```python
|
| 87 |
+
from jang_tools.load_jangtq import load_jangtq_model
|
| 88 |
+
from mlx_lm import generate
|
| 89 |
+
|
| 90 |
+
model, tokenizer = load_jangtq_model("JANGQ-AI/Holo3-35B-A3B-JANGTQ2")
|
| 91 |
+
print(generate(model, tokenizer,
|
| 92 |
+
prompt="The capital of France is",
|
| 93 |
+
max_tokens=64))
|
| 94 |
+
```
|
| 95 |
+
|
| 96 |
+
### Image (VLM) — the intended use
|
| 97 |
+
|
| 98 |
+
Holo3 is a GUI agent: give it a screenshot and it localizes UI elements and plans actions.
|
| 99 |
+
|
| 100 |
+
```python
|
| 101 |
+
from jang_tools.load_jangtq_vlm import load_jangtq_vlm_model
|
| 102 |
+
from mlx_vlm import generate
|
| 103 |
+
from mlx_vlm.prompt_utils import apply_chat_template
|
| 104 |
+
from mlx_vlm.utils import load_config
|
| 105 |
+
|
| 106 |
+
path = "JANGQ-AI/Holo3-35B-A3B-JANGTQ2"
|
| 107 |
+
model, processor = load_jangtq_vlm_model(path)
|
| 108 |
+
config = load_config(path)
|
| 109 |
+
|
| 110 |
+
prompt = apply_chat_template(
|
| 111 |
+
processor, config,
|
| 112 |
+
"Look at this desktop screenshot. Where should I click to open settings?",
|
| 113 |
+
num_images=1,
|
| 114 |
+
)
|
| 115 |
+
print(generate(model, processor, prompt, image="path/to/screenshot.png",
|
| 116 |
+
max_tokens=256))
|
| 117 |
+
```
|
| 118 |
+
|
| 119 |
+
### Reasoning toggle
|
| 120 |
+
|
| 121 |
+
```python
|
| 122 |
+
msgs = [{"role": "user", "content": "What is 17 × 23?"}]
|
| 123 |
+
# Reasoning OFF — pre-closed <think></think> block
|
| 124 |
+
prompt = tokenizer.apply_chat_template(msgs, add_generation_prompt=True,
|
| 125 |
+
enable_thinking=False)
|
| 126 |
+
# Reasoning ON — model fills the <think> block
|
| 127 |
+
prompt = tokenizer.apply_chat_template(msgs, add_generation_prompt=True,
|
| 128 |
+
enable_thinking=True)
|
| 129 |
+
```
|
| 130 |
+
|
| 131 |
+
Pass `enable_thinking` as a **direct kwarg** (the `chat_template_kwargs={...}` form only propagates on some tokenizer versions).
|
| 132 |
+
|
| 133 |
+
### Tool calls — Holo3 XML format
|
| 134 |
+
|
| 135 |
+
Holo3 emits tool calls in a custom XML grammar (not JSON). Pass `tools=[...]` to the tokenizer's chat template; the model responds in this shape:
|
| 136 |
+
|
| 137 |
+
```xml
|
| 138 |
+
<tool_call>
|
| 139 |
+
<function=click>
|
| 140 |
+
<parameter=x>
|
| 141 |
+
512
|
| 142 |
+
</parameter>
|
| 143 |
+
<parameter=y>
|
| 144 |
+
384
|
| 145 |
+
</parameter>
|
| 146 |
+
</function>
|
| 147 |
+
</tool_call>
|
| 148 |
+
```
|
| 149 |
+
|
| 150 |
+
Parse with a simple XML splitter on `<tool_call>`. See H Company's [quickstart](https://hub.hcompany.ai/quickstart) for a full agent harness example.
|
| 151 |
+
|
| 152 |
+
### Video
|
| 153 |
+
|
| 154 |
+
The base model supports video via `transformers` and the bundle preserves `video_preprocessor_config.json`. `mlx-vlm` 0.4.4's `prepare_inputs` has no video path yet for `qwen3_5_moe` — for video, use upstream `transformers`.
|
| 155 |
+
|
| 156 |
+
---
|
| 157 |
+
|
| 158 |
+
## Hardware notes
|
| 159 |
+
|
| 160 |
+
`11.63 GB` on disk; expect ~12–14 GB resident after load, plus KV cache.
|
| 161 |
+
|
| 162 |
+
| Mac unified RAM | Works? | Notes |
|
| 163 |
+
|---|---|---|
|
| 164 |
+
| 16 GB | ✅ text-only | Image inference will be tight at long context |
|
| 165 |
+
| 24 GB | ✅ comfortable | 32 k+ context, image inference OK |
|
| 166 |
+
| 32 GB | ✅ | 100 k context viable, comfortable VL |
|
| 167 |
+
| 64 GB+ | ✅ headroom | 262 k native context |
|
| 168 |
+
|
| 169 |
+
---
|
| 170 |
+
|
| 171 |
+
## Upstream benchmarks
|
| 172 |
+
|
| 173 |
+
These are the base-model numbers for `Hcompany/Holo3-35B-A3B`, not evaluations of this JANGTQ2 quant:
|
| 174 |
+
|
| 175 |
+
| Benchmark | Score |
|
| 176 |
+
|---|---|
|
| 177 |
+
| **OSWorld-Verified** (computer use) | **77.8 %** — SOTA at 3 B active |
|
| 178 |
+
| WebArena (web navigation) | State-of-the-art (see upstream card) |
|
| 179 |
+
| ScreenSpot-Pro (UI localization) | Top-tier (see upstream card) |
|
| 180 |
+
| OSWorld-G (visual grounding) | Top-tier (see upstream card) |
|
| 181 |
+
| H Corporate Benchmark (486 enterprise tasks) | Outperforms larger competitors |
|
| 182 |
+
|
| 183 |
+
Independent JANGTQ-quant evaluation is tracked in the jang-tools repo and will land in future README revisions.
|
| 184 |
+
|
| 185 |
+
---
|
| 186 |
+
|
| 187 |
+
## Citation
|
| 188 |
+
|
| 189 |
+
```bibtex
|
| 190 |
+
@misc{hai2025holo3modelfamily,
|
| 191 |
+
title = {Holo3 - Open Foundation Models for Navigation and Computer Use Agents},
|
| 192 |
+
author = {H Company},
|
| 193 |
+
year = {2026},
|
| 194 |
+
url = {https://huggingface.co/Hcompany/Holo3-35B-A3B}
|
| 195 |
+
}
|
| 196 |
+
```
|
| 197 |
+
|
| 198 |
+
## License
|
| 199 |
+
|
| 200 |
+
[Apache 2.0](https://huggingface.co/Hcompany/Holo3-35B-A3B/blob/main/LICENSE) — inherits from the base model.
|
| 201 |
+
|
| 202 |
+
---
|
| 203 |
+
|
| 204 |
+
<p align="center">
|
| 205 |
+
Packaged on Apple Silicon with <a href="https://github.com/jjang-ai/jangq">jang-tools</a> (mlx-lm 0.31.2) by Jinho Jang (<a href="mailto:eric@jangq.ai">eric@jangq.ai</a>).<br>
|
| 206 |
+
© 2026 Osaurus AI — <a href="https://osaurus.ai">osaurus.ai</a>
|
| 207 |
+
</p>
|
chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
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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 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\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>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
config.json
ADDED
|
@@ -0,0 +1,129 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"Qwen3_5MoeForConditionalGeneration"
|
| 4 |
+
],
|
| 5 |
+
"dtype": "float32",
|
| 6 |
+
"image_token_id": 248056,
|
| 7 |
+
"model_type": "qwen3_5_moe",
|
| 8 |
+
"text_config": {
|
| 9 |
+
"attention_bias": false,
|
| 10 |
+
"attention_dropout": 0.0,
|
| 11 |
+
"attn_output_gate": true,
|
| 12 |
+
"bos_token_id": null,
|
| 13 |
+
"dtype": "float32",
|
| 14 |
+
"eos_token_id": 248044,
|
| 15 |
+
"full_attention_interval": 4,
|
| 16 |
+
"head_dim": 256,
|
| 17 |
+
"hidden_act": "silu",
|
| 18 |
+
"hidden_size": 2048,
|
| 19 |
+
"initializer_range": 0.02,
|
| 20 |
+
"layer_types": [
|
| 21 |
+
"linear_attention",
|
| 22 |
+
"linear_attention",
|
| 23 |
+
"linear_attention",
|
| 24 |
+
"full_attention",
|
| 25 |
+
"linear_attention",
|
| 26 |
+
"linear_attention",
|
| 27 |
+
"linear_attention",
|
| 28 |
+
"full_attention",
|
| 29 |
+
"linear_attention",
|
| 30 |
+
"linear_attention",
|
| 31 |
+
"linear_attention",
|
| 32 |
+
"full_attention",
|
| 33 |
+
"linear_attention",
|
| 34 |
+
"linear_attention",
|
| 35 |
+
"linear_attention",
|
| 36 |
+
"full_attention",
|
| 37 |
+
"linear_attention",
|
| 38 |
+
"linear_attention",
|
| 39 |
+
"linear_attention",
|
| 40 |
+
"full_attention",
|
| 41 |
+
"linear_attention",
|
| 42 |
+
"linear_attention",
|
| 43 |
+
"linear_attention",
|
| 44 |
+
"full_attention",
|
| 45 |
+
"linear_attention",
|
| 46 |
+
"linear_attention",
|
| 47 |
+
"linear_attention",
|
| 48 |
+
"full_attention",
|
| 49 |
+
"linear_attention",
|
| 50 |
+
"linear_attention",
|
| 51 |
+
"linear_attention",
|
| 52 |
+
"full_attention",
|
| 53 |
+
"linear_attention",
|
| 54 |
+
"linear_attention",
|
| 55 |
+
"linear_attention",
|
| 56 |
+
"full_attention",
|
| 57 |
+
"linear_attention",
|
| 58 |
+
"linear_attention",
|
| 59 |
+
"linear_attention",
|
| 60 |
+
"full_attention"
|
| 61 |
+
],
|
| 62 |
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"linear_conv_kernel_dim": 4,
|
| 63 |
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"linear_key_head_dim": 128,
|
| 64 |
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"linear_num_key_heads": 16,
|
| 65 |
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|
| 66 |
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"linear_value_head_dim": 128,
|
| 67 |
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"mamba_ssm_dtype": "float32",
|
| 68 |
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"max_position_embeddings": 262144,
|
| 69 |
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"mlp_only_layers": [],
|
| 70 |
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"model_type": "qwen3_5_moe_text",
|
| 71 |
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"moe_intermediate_size": 512,
|
| 72 |
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"mtp_num_hidden_layers": 1,
|
| 73 |
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"mtp_use_dedicated_embeddings": false,
|
| 74 |
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|
| 75 |
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"num_experts": 256,
|
| 76 |
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"num_experts_per_tok": 8,
|
| 77 |
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|
| 78 |
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"num_key_value_heads": 2,
|
| 79 |
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"output_router_logits": false,
|
| 80 |
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"pad_token_id": null,
|
| 81 |
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"partial_rotary_factor": 0.25,
|
| 82 |
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"rms_norm_eps": 1e-06,
|
| 83 |
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"rope_parameters": {
|
| 84 |
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"mrope_interleaved": true,
|
| 85 |
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"mrope_section": [
|
| 86 |
+
11,
|
| 87 |
+
11,
|
| 88 |
+
10
|
| 89 |
+
],
|
| 90 |
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"partial_rotary_factor": 0.25,
|
| 91 |
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"rope_theta": 10000000,
|
| 92 |
+
"rope_type": "default"
|
| 93 |
+
},
|
| 94 |
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"router_aux_loss_coef": 0.001,
|
| 95 |
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"shared_expert_intermediate_size": 512,
|
| 96 |
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"tie_word_embeddings": false,
|
| 97 |
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"use_cache": true,
|
| 98 |
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"vocab_size": 248320
|
| 99 |
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},
|
| 100 |
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"tie_word_embeddings": false,
|
| 101 |
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"transformers_version": "5.2.0",
|
| 102 |
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"video_token_id": 248057,
|
| 103 |
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"vision_config": {
|
| 104 |
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"deepstack_visual_indexes": [],
|
| 105 |
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"depth": 27,
|
| 106 |
+
"dtype": "float32",
|
| 107 |
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"hidden_act": "gelu_pytorch_tanh",
|
| 108 |
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"hidden_size": 1152,
|
| 109 |
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"in_channels": 3,
|
| 110 |
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|
| 111 |
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"intermediate_size": 4304,
|
| 112 |
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"model_type": "qwen3_5_moe",
|
| 113 |
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|
| 114 |
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|
| 115 |
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|
| 116 |
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"patch_size": 16,
|
| 117 |
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"spatial_merge_size": 2,
|
| 118 |
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"temporal_patch_size": 2
|
| 119 |
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},
|
| 120 |
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"vision_end_token_id": 248054,
|
| 121 |
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|
| 122 |
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"quantization": {
|
| 123 |
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|
| 124 |
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"bits": 2
|
| 125 |
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},
|
| 126 |
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"weight_format": "mxtq",
|
| 127 |
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"mxtq_seed": 42,
|
| 128 |
+
"mxtq_bits": 2
|
| 129 |
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}
|
generation_config.json
ADDED
|
@@ -0,0 +1,13 @@
|
|
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|
|
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|
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|
| 1 |
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{
|
| 2 |
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"bos_token_id": 248044,
|
| 3 |
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"do_sample": true,
|
| 4 |
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"eos_token_id": [
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| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
jang_config.json
ADDED
|
@@ -0,0 +1,34 @@
|
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|
| 1 |
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{
|
| 2 |
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"version": 2,
|
| 3 |
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"weight_format": "mxtq",
|
| 4 |
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"profile": "JANGTQ2",
|
| 5 |
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"source_model": {
|
| 6 |
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"name": "Holo3-35B-A3B",
|
| 7 |
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"architecture": "qwen3_5_moe_text"
|
| 8 |
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},
|
| 9 |
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"has_vision": true,
|
| 10 |
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|
| 11 |
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|
| 12 |
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"attention": 8,
|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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"method": "affine+mxtq",
|
| 21 |
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|
| 22 |
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|
| 23 |
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},
|
| 24 |
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"capabilities": {
|
| 25 |
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"reasoning_parser": "qwen3",
|
| 26 |
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"tool_parser": "qwen",
|
| 27 |
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"think_in_template": true,
|
| 28 |
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"supports_tools": true,
|
| 29 |
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"supports_thinking": true,
|
| 30 |
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"family": "qwen3_5_moe",
|
| 31 |
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"modality": "vision",
|
| 32 |
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"cache_type": "hybrid"
|
| 33 |
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|
| 34 |
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jangtq_runtime.safetensors
ADDED
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ADDED
|
preprocessor_config.json
ADDED
|
@@ -0,0 +1,21 @@
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{
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"image_processor_type": "Qwen2VLImageProcessorFast"
|
| 21 |
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tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
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tokenizer_config.json
ADDED
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@@ -0,0 +1,305 @@
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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{%- if tools and tools is iterable and tools is not mapping %}\n {{- '<|im_start|>system\\n' }}\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 {{- '<|im_start|>system\\n' + content + '<|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 {%- else %}\n {%- if '</think>' in content %}\n {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n {%- endif %}\n {%- endif %}\n {%- set reasoning_content = reasoning_content|trim %}\n {%- if 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 %}\n {%- for args_name, args_value in tool_call.arguments|items %}\n {{- '<parameter=' + args_name + '>\\n' }}\n {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}\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
|
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|