NVFP4 GPTQ, thinking-mode calib, bf16 MTP head, scale packaging verified

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,184 @@
+---
+license: apache-2.0
+base_model: Qwen/Qwen3.8-27B
+base_model_relation: quantized
+library_name: transformers
+pipeline_tag: image-text-to-text
+tags:
+  - qwen3.8
+  - qwen3_5
+  - nvfp4
+  - fp4
+  - compressed-tensors
+  - mtp
+  - vision
+  - thinking
+  - v100
+---
+
+# Qwen3.8-27B — NVFP4
+
+<p>
+  <img src="https://img.shields.io/badge/weights-NVFP4%20(FP4)-2a78d6" alt="NVFP4">
+  <img src="https://img.shields.io/badge/size-19.8%20GB-2a78d6" alt="19.8 GB">
+  <img src="https://img.shields.io/badge/vision-intact-1baf7a" alt="vision intact">
+  <img src="https://img.shields.io/badge/MTP-BF16%20head-1baf7a" alt="MTP BF16 head">
+  <img src="https://img.shields.io/badge/V100%20%C3%972-serves-1baf7a" alt="2xV100">
+  <img src="https://img.shields.io/badge/license-Apache--2.0-52514e" alt="Apache 2.0">
+</p>
+
+NVFP4 (4-bit floating point, weight-only) quantization of
+[Qwen/Qwen3.8-27B](https://huggingface.co/Qwen/Qwen3.8-27B) — **the whole model, nothing
+stripped**: vision tower intact, MTP speculative-decoding head intact in BF16, thinking mode
+calibrated with real reasoning traces. 55 GB BF16 → **19.8 GB**.
+
+Built as `compressed-tensors` **nvfp4-pack-quantized** deliberately: 1Cat-vLLM's SM70 NVFP4
+path accepts this format at compute capability **7.0**, so it serves on
+**2×V100-32GB under [1Cat-vLLM](https://github.com/rivetphilbot/1Cat-vLLM) 1.2.2** — whereas
+ModelOpt-exported NVFP4 checkpoints require capability 7.5+ and reject Volta. On SM100+
+(Blackwell) the FP4 tensor cores run this format natively.
+
+## At a glance
+
+| | |
+|---|---|
+| **Base model** | Qwen/Qwen3.8-27B — dense 27B vision-language model, 64 layers (16 full-attention + 48 GatedDeltaNet linear-attention), thinking on by default |
+| **Format** | `compressed-tensors` **nvfp4-pack-quantized** — E2M1 4-bit weights, FP8-E4M3 per-group scales (group 16), FP32 per-tensor global scale, weight-only |
+| **Method** | GPTQ (Hessian-based, sequential over `Qwen3_5DecoderLayer`) |
+| **Files** | `model.safetensors` 19.0 GB (packed body) + `model-mtp.safetensors` 0.83 GB (BF16 MTP head) |
+| **Quantized** | 400 linears — all attention + MLP projections, incl. 144 GatedDeltaNet projections |
+| **Kept in BF16** | vision tower (333 tensors) · `linear_attn.in_proj_a/b` · `embed_tokens` · `lm_head` · MTP head |
+| **Context length** | 262,144 native · extensible to 1M with YaRN (see below) |
+| **Reference hardware** | 2×V100-32GB (TP2) via 1Cat-vLLM 1.2.2 · native FP4 on SM100+ |
+
+## Measured performance
+
+Benchmarks on 2×V100-32GB (1Cat-vLLM 1.2.2, TP2, `fp8_e5m2` KV, official Qwen3.8 thinking-mode
+sampling) are being run now — multi-pass, warm-serve methodology, MTP K=2 in both draft modes.
+This section will be updated with the results and a throughput chart.
+
+## The base model
+
+Qwen3.8-27B is the compact dense model of the Qwen3.8 generation: a native vision-language model
+with flexible thinking control (`reasoning_effort`, `preserve_thinking`), built for long-horizon
+agentic work. The hidden layout is 16 blocks of `3×(GatedDeltaNet→FFN) → 1×(GatedAttention→FFN)`.
+
+Official base-model (BF16) benchmarks, from the
+[Qwen3.8-27B model card](https://huggingface.co/Qwen/Qwen3.8-27B) — quantization applies on top
+of these; they are not re-measured on this checkpoint:
+
+| Benchmark | Qwen3.8-27B | Qwen3.6-27B |
+|---|---|---|
+| Terminal Bench 2.1 (Terminus) | **73.0** | 63.4 |
+| SWE-bench Pro | 53.5 | 57.6 |
+| NL2Repo-Bench | **42.3** | 36.2 |
+| GPQA Diamond | **89.2** | 87.8 |
+| HLE | **30.8** | 24.0 |
+| LiveCodeBench v6 | 83.9 | 89.6 |
+| IFBench | 69.1 | 79.1 |
+| OmniDocBench 1.5 *(VL)* | **91.1** | 89.4 |
+| RealWorldQA *(VL)* | **85.9** | 84.1 |
+| ERQA *(VL)* | **65.5** | 62.5 |
+| OSWorld-Verified *(VL)* | 63.9 | 73.3 |
+
+## Why this build is careful
+
+### Thinking-mode calibration
+
+Qwen3.8 deploys with thinking **on** by default — so this quant was calibrated in thinking mode.
+256 samples @ 2048 tokens of real `<think>…</think>` reasoning traces from
+[Magpie-Reasoning-V2-250K-CoT](https://huggingface.co/datasets/Magpie-Align/Magpie-Reasoning-V2-250K-CoT-Deepseek-R1-Llama-70B)
+(filtered to complete traces), applied with `enable_thinking=True`. Calibrating a thinking model
+with `enable_thinking=False` shows the quantizer an *empty* think block on every sample — a
+calibration/deployment mismatch documented to corrupt `<think>`-tag behavior after quantization
+(llm-compressor [#2680](https://github.com/vllm-project/llm-compressor/issues/2680) /
+[#2681](https://github.com/vllm-project/llm-compressor/pull/2681)).
+
+### Scale packaging, verified
+
+NVFP4 dequant is `w = e2m1 × weight_scale / weight_global_scale`. This build stores the fp8
+block scales **with the global factor folded in** (block-scale max saturates fp8 at 448.0,
+FP32 global per tensor) — the packaging convention verified against known-good checkpoints.
+GPTQ Hessian calibration ran on the same thinking-mode dataset as the weight quantization.
+
+### MTP head — BF16 by design
+
+The base model's 15-tensor MTP head is grafted back **verbatim in BF16** as
+`model-mtp.safetensors` and listed in `quantization_config.ignore`. High-precision MTP heads are
+standard NVFP4 practice (NVIDIA's ModelOpt recipes do the same): the head drives speculative
+decoding, where draft quality directly sets acceptance rate. One MTP layer; K=2 is the sweet
+spot on V100.
+
+## Serving
+
+### 2×V100 / SM70 — 1Cat-vLLM 1.2.2
+
+```bash
+VLLM_SM70_QUANT_BACKEND=turbomind VLLM_SM70_FLASH_ATTN_V100=1 VLLM_SM70_NVFP4_TURBOMIND=1 \
+VLLM_SM70_MTP_DYNAMIC_DRAFT_VOCAB_DEFAULT=0 NCCL_P2P_DISABLE=1 \
+python -m vllm.entrypoints.openai.api_server \
+  --model philbert440/Qwen3.8-27B-NVFP4 \
+  --dtype half --attention-backend FLASH_ATTN_V100 \
+  --tensor-parallel-size 2 --gpu-memory-utilization 0.78 \
+  --max-model-len 32768 --kv-cache-dtype fp8_e5m2 \
+  --enable-prefix-caching --reasoning-parser qwen3 \
+  --speculative-config '{"method":"mtp","num_speculative_tokens":2,"attention_backend":"FLASH_ATTN_V100","draft_sample_method":"greedy"}'
+```
+
+SM70 notes, learned the hard way:
+
+- `ninja` must be on `PATH` — the dequant kernels JIT-compile at startup.
+- `VLLM_SM70_MTP_DYNAMIC_DRAFT_VOCAB_DEFAULT=0` is required for `max_num_seqs > 1` with MTP.
+- `NCCL_P2P_DISABLE=1` on V100 pairs without NVLink — leaving P2P on costs ~4× throughput.
+- Boot takes ~3–5 min (weight load + `torch.compile` + CUDA graph capture); poll `/v1/models`.
+
+### Modern GPUs
+
+On SM100+ the compressed-tensors NVFP4 format runs on native FP4 tensor cores in recent vLLM;
+on Ampere/Hopper it runs via dequant paths (Marlin). If you only need Ampere+, consider the
+[W4A16-AWQ sibling](https://huggingface.co/philbert440/Qwen3.8-27B-W4A16-AWQ) as well.
+
+## Recommended sampling (official)
+
+| Mode | temperature | top_p | top_k | min_p | presence_penalty |
+|---|---|---|---|---|---|
+| Thinking (default) | 1.0 | 0.95 | 20 | 0.0 | 0.0 |
+| Instruct (non-thinking) | 0.7 | 0.80 | 20 | 0.0 | 1.5 |
+
+Thinking is on by default; disable per request with
+`"chat_template_kwargs": {"enable_thinking": false}`. For agentic work, give it generous output
+budgets rather than tight `max_tokens` limits.
+
+## Long context — 262K native, 1M with YaRN
+
+Native 262,144-token context. For longer totals, Qwen's official YaRN override applies:
+
+```bash
+VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 vllm serve philbert440/Qwen3.8-27B-NVFP4 \
+  --max-model-len 1000000 \
+  --hf-overrides '{"text_config": {"rope_parameters": {"mrope_interleaved": true, "mrope_section": [11, 11, 10], "rope_type": "yarn", "rope_theta": 10000000, "partial_rotary_factor": 0.25, "factor": 4.0, "original_max_position_embeddings": 262144}}}'
+```
+
+Static YaRN can slightly hurt short-text quality — enable only when needed, and size `factor`
+to your real context.
+
+## Provenance
+
+Quantized from the official BF16 release with
+[llm-compressor](https://github.com/vllm-project/llm-compressor) (`GPTQModifier`, recipe in
+`recipe.yaml`). No fine-tuning, no ablation, no chat-template edits — tokenizer, chat template,
+and preprocessor configs are verbatim from the base model.
+
+## Citation
+
+Per the Qwen team, for the base model:
+
+```bibtex
+@misc{qwen38,
+    title = {{Qwen3.8-Max}: A New Bar for Coding and Cowork},
+    url = {https://qwen.ai/blog?id=qwen3.8},
+    author = {{Qwen Team}},
+    month = {August},
+    year = {2026}
+}
+```

chat_template.jinja

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+{%- set image_count = namespace(value=0) %}
+{%- set video_count = namespace(value=0) %}
+{%- macro render_content(content, do_vision_count, is_system_content=false) %}
+    {%- if content is string %}
+        {{- content }}
+    {%- elif content is iterable and content is not mapping %}
+        {%- for item in content %}
+            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain images.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set image_count.value = image_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Picture ' ~ image_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
+            {%- elif 'video' in item or item.type == 'video' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain videos.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set video_count.value = video_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Video ' ~ video_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
+            {%- elif 'text' in item %}
+                {{- item.text }}
+            {%- else %}
+                {{- raise_exception('Unexpected item type in content.') }}
+            {%- endif %}
+        {%- endfor %}
+    {%- elif content is none or content is undefined %}
+        {{- '' }}
+    {%- else %}
+        {{- raise_exception('Unexpected content type.') }}
+    {%- endif %}
+{%- endmacro %}
+{%- if not messages %}
+    {{- raise_exception('No messages provided.') }}
+{%- endif %}
+{%- set reasoning_instructions = '' %}
+{%- if enable_thinking is undefined or enable_thinking is true %}
+    {%- set resolved_reasoning_effort = reasoning_effort|default('xhigh') %}
+    {%- if resolved_reasoning_effort not in ('xhigh', 'medium', 'low') %}
+        {{- raise_exception('Unexpected reasoning effort ' ~ reasoning_effort ~ '. Supported types are xhigh (default), medium, and low.') }}
+    {%- endif %}
+    {%- if resolved_reasoning_effort == 'xhigh' %}
+        {%- 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.' %}
+    {%- elif resolved_reasoning_effort == 'low' %}
+        {%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}
+    {%- endif %}
+{%- endif %}
+{%- if tools and tools is iterable and tools is not mapping %}
+    {{- '<|im_start|>system\n' }}
+    {%- if reasoning_instructions %}
+        {{- reasoning_instructions + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>" }}
+    {{- '\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>' }}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {%- if content %}
+            {{- '\n\n' + content }}
+        {%- endif %}
+    {%- endif %}
+    {{- '<|im_end|>\n' }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {%- if content %}
+            {{- '<|im_start|>system\n' + (reasoning_instructions + '\n\n' if reasoning_instructions else '')  + content + '<|im_end|>\n' }}
+        {%- elif reasoning_instructions %}
+            {{- '<|im_start|>system\n' + reasoning_instructions + '<|im_end|>\n' }}
+        {%- endif %}
+    {%- elif reasoning_instructions %}
+        {{- '<|im_start|>system\n' + reasoning_instructions + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" %}
+        {%- set content = render_content(message.content, false)|trim %}
+        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
+            {%- set ns.multi_step_tool = false %}
+            {%- set ns.last_query_index = index %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if ns.multi_step_tool %}
+    {{- raise_exception('No user query found in messages.') }}
+{%- endif %}
+{%- for message in messages %}
+    {%- set content = render_content(message.content, true)|trim %}
+    {%- if message.role == "system" %}
+        {%- if not loop.first %}
+            {{- raise_exception('System message must be at the beginning.') }}
+        {%- endif %}
+    {%- elif message.role == "user" %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- endif %}
+        {%- set reasoning_content = reasoning_content|trim %}
+        {%- if preserve_thinking is undefined or preserve_thinking is true or loop.index0 > ns.last_query_index %}
+            {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if tool_call.function is defined %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {%- if loop.first %}
+                    {%- if content|trim %}
+                        {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- else %}
+                        {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- endif %}
+                {%- else %}
+                    {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                {%- endif %}
+                {%- if tool_call.arguments is defined and tool_call.arguments != '' %}
+                    {%- for args_name, args_value in tool_call.arguments|items %}
+                        {{- '<parameter=' + args_name + '>\n' }}
+                        {%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}
+                        {{- args_value }}
+                        {{- '\n</parameter>\n' }}
+                    {%- endfor %}
+                {%- endif %}
+                {{- '</function>\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.previtem and loop.previtem.role != "tool" %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if not loop.last and loop.nextitem.role != "tool" %}
+            {{- '<|im_end|>\n' }}
+        {%- elif loop.last %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- else %}
+        {{- raise_exception('Unexpected message role.') }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- else %}
+        {{- '<think>\n' }}
+    {%- endif %}
+{%- endif %}

config.json

@@ -0,0 +1,489 @@
+{
+  "architectures": [
+    "Qwen3_5ForConditionalGeneration"
+  ],
+  "dtype": "bfloat16",
+  "image_token_id": 248056,
+  "language_model_only": false,
+  "model_type": "qwen3_5",
+  "quantization_config": {
+    "config_groups": {
+      "group_0": {
+        "format": "nvfp4-pack-quantized",
+        "input_activations": null,
+        "output_activations": null,
+        "targets": [
+          "Linear"
+        ],
+        "weights": {
+          "actorder": "static",
+          "block_structure": null,
+          "dynamic": false,
+          "group_size": 16,
+          "num_bits": 4,
+          "observer": "memoryless_minmax",
+          "observer_kwargs": {},
+          "scale_dtype": "torch.float8_e4m3fn",
+          "strategy": "tensor_group",
+          "symmetric": true,
+          "type": "float",
+          "zp_dtype": null
+        }
+      }
+    },
+    "format": "nvfp4-pack-quantized",
+    "global_compression_ratio": null,
+    "ignore": [
+      "model.visual.blocks.0.attn.qkv",
+      "model.visual.blocks.0.attn.proj",
+      "model.visual.blocks.0.mlp.linear_fc1",
+      "model.visual.blocks.0.mlp.linear_fc2",
+      "model.visual.blocks.1.attn.qkv",
+      "model.visual.blocks.1.attn.proj",
+      "model.visual.blocks.1.mlp.linear_fc1",
+      "model.visual.blocks.1.mlp.linear_fc2",
+      "model.visual.blocks.2.attn.qkv",
+      "model.visual.blocks.2.attn.proj",
+      "model.visual.blocks.2.mlp.linear_fc1",
+      "model.visual.blocks.2.mlp.linear_fc2",
+      "model.visual.blocks.3.attn.qkv",
+      "model.visual.blocks.3.attn.proj",
+      "model.visual.blocks.3.mlp.linear_fc1",
+      "model.visual.blocks.3.mlp.linear_fc2",
+      "model.visual.blocks.4.attn.qkv",
+      "model.visual.blocks.4.attn.proj",
+      "model.visual.blocks.4.mlp.linear_fc1",
+      "model.visual.blocks.4.mlp.linear_fc2",
+      "model.visual.blocks.5.attn.qkv",
+      "model.visual.blocks.5.attn.proj",
+      "model.visual.blocks.5.mlp.linear_fc1",
+      "model.visual.blocks.5.mlp.linear_fc2",
+      "model.visual.blocks.6.attn.qkv",
+      "model.visual.blocks.6.attn.proj",
+      "model.visual.blocks.6.mlp.linear_fc1",
+      "model.visual.blocks.6.mlp.linear_fc2",
+      "model.visual.blocks.7.attn.qkv",
+      "model.visual.blocks.7.attn.proj",
+      "model.visual.blocks.7.mlp.linear_fc1",
+      "model.visual.blocks.7.mlp.linear_fc2",
+      "model.visual.blocks.8.attn.qkv",
+      "model.visual.blocks.8.attn.proj",
+      "model.visual.blocks.8.mlp.linear_fc1",
+      "model.visual.blocks.8.mlp.linear_fc2",
+      "model.visual.blocks.9.attn.qkv",
+      "model.visual.blocks.9.attn.proj",
+      "model.visual.blocks.9.mlp.linear_fc1",
+      "model.visual.blocks.9.mlp.linear_fc2",
+      "model.visual.blocks.10.attn.qkv",
+      "model.visual.blocks.10.attn.proj",
+      "model.visual.blocks.10.mlp.linear_fc1",
+      "model.visual.blocks.10.mlp.linear_fc2",
+      "model.visual.blocks.11.attn.qkv",
+      "model.visual.blocks.11.attn.proj",
+      "model.visual.blocks.11.mlp.linear_fc1",
+      "model.visual.blocks.11.mlp.linear_fc2",
+      "model.visual.blocks.12.attn.qkv",
+      "model.visual.blocks.12.attn.proj",
+      "model.visual.blocks.12.mlp.linear_fc1",
+      "model.visual.blocks.12.mlp.linear_fc2",
+      "model.visual.blocks.13.attn.qkv",
+      "model.visual.blocks.13.attn.proj",
+      "model.visual.blocks.13.mlp.linear_fc1",
+      "model.visual.blocks.13.mlp.linear_fc2",
+      "model.visual.blocks.14.attn.qkv",
+      "model.visual.blocks.14.attn.proj",
+      "model.visual.blocks.14.mlp.linear_fc1",
+      "model.visual.blocks.14.mlp.linear_fc2",
+      "model.visual.blocks.15.attn.qkv",
+      "model.visual.blocks.15.attn.proj",
+      "model.visual.blocks.15.mlp.linear_fc1",
+      "model.visual.blocks.15.mlp.linear_fc2",
+      "model.visual.blocks.16.attn.qkv",
+      "model.visual.blocks.16.attn.proj",
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generation_config.json

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+{
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+  "do_sample": true,
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+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "5.15.0"
+}

model-mtp.safetensors

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+size 849400424

model.safetensors

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preprocessor_config.json

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+}

recipe.yaml

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+        model.visual.blocks.1.mlp.linear_fc1, model.visual.blocks.1.mlp.linear_fc2, model.visual.blocks.2.attn.qkv,
+        model.visual.blocks.2.attn.proj, model.visual.blocks.2.mlp.linear_fc1, model.visual.blocks.2.mlp.linear_fc2,
+        model.visual.blocks.3.attn.qkv, model.visual.blocks.3.attn.proj, model.visual.blocks.3.mlp.linear_fc1,
+        model.visual.blocks.3.mlp.linear_fc2, model.visual.blocks.4.attn.qkv, model.visual.blocks.4.attn.proj,
+        model.visual.blocks.4.mlp.linear_fc1, model.visual.blocks.4.mlp.linear_fc2, model.visual.blocks.5.attn.qkv,
+        model.visual.blocks.5.attn.proj, model.visual.blocks.5.mlp.linear_fc1, model.visual.blocks.5.mlp.linear_fc2,
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+        model.language_model.layers.62.linear_attn.in_proj_a, lm_head, mtp.fc]
+      scheme: NVFP4A16
+      bypass_divisibility_checks: false
+      requires_calibration_data: true
+      block_size: 128
+      dampening_frac: 0.01
+      actorder: static
+      offload_hessians: false

tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f399b3cd12fa270d51457bb749fb30863521e8359b8a27059c71b6c2f7d6dd6c
+size 19989424

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "audio_bos_token": "<|audio_start|>",
+  "audio_eos_token": "<|audio_end|>",
+  "audio_token": "<|audio_pad|>",
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
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+  "is_local": true,
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+    "audio_token": "<|audio_pad|>",
+    "image_token": "<|image_pad|>",
+    "video_token": "<|video_pad|>",
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+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
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+  "video_token": "<|video_pad|>",
+  "vision_bos_token": "<|vision_start|>",
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+}

video_preprocessor_config.json

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+{
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+        "shortest_edge": 4096
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+    "temporal_patch_size": 2,
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+    "processor_class": "Qwen3VLProcessor",
+    "video_processor_type": "Qwen3VLVideoProcessor"
+}