Initial release: NVFP4 + MTP head bf16-restored, text-only

.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 +1,105 @@
+---
+license: apache-2.0
+base_model: Qwen/Qwen3.6-27B
+base_model_relation: quantized
+library_name: transformers
+tags:
+  - qwen3_5
+  - qwen3.6
+  - nvfp4
+  - quantized
+  - modelopt
+  - mtp
+  - speculative-decoding
+  - blackwell
+  - text-only
+pipeline_tag: text-generation
+language:
+  - en
+  - zh
+  - ja
+  - ko
+  - fr
+  - de
+  - es
+  - it
+  - pt
+  - ru
+  - ar
+---
+
+# Qwen3.6-27B-Text-NVFP4-MTP
+
+NVFP4-quantized text-only sibling of [`Qwen/Qwen3.6-27B`](https://huggingface.co/Qwen/Qwen3.6-27B), with the **MTP (Multi-Token Prediction) head restored in bf16** so speculative decoding actually works.
+
+## What's different from `sakamakismile/Qwen3.6-27B-NVFP4`
+
+| | This repo (`-Text-NVFP4-MTP`) | `Qwen3.6-27B-NVFP4` |
+|---|---|---|
+| Quantization format | **`modelopt`** (vLLM SM120 native path) | `compressed-tensors` |
+| MTP head | **Restored in bf16, working** | Dropped during export → 0% draft acceptance |
+| Vision tower | **Stripped (text-only)** | Present (kept for VLM use) |
+| Suggested launch | with `--speculative-config` | without speculation |
+
+The original `Qwen3.6-27B-NVFP4` is left untouched so existing users (~15K downloads) are not disrupted. This is a focused text-only sibling for users who want maximum speed and don't need vision input.
+
+## Why this exists
+
+Two HF Discussion threads on the original repo prompted this:
+
+- [#5 — slower than official FP8 on Blackwell](https://huggingface.co/sakamakismile/Qwen3.6-27B-NVFP4/discussions/5) — root cause is the `compressed-tensors` NVFP4 path being slower than `modelopt` on Blackwell SM120; this repo uses `modelopt` natively.
+- [#7 — MTP not responding](https://huggingface.co/sakamakismile/Qwen3.6-27B-NVFP4/discussions/7) — `AutoModelForCausalLM.from_pretrained` does not load the MTP head, so it gets dropped during quantization, leading to 0% draft acceptance. This repo grafts the 15 `mtp.*` tensors (bf16) back into the quantized checkpoint and adds them to the quantization ignore list.
+
+Recipe is adapted from [`osoleve/Qwen3.5-27B-Text-NVFP4-MTP`](https://huggingface.co/osoleve/Qwen3.5-27B-Text-NVFP4-MTP) — credit and thanks.
+
+## Quantization details
+
+- **Base**: `Qwen/Qwen3.6-27B` (bf16, 27.78B params, hybrid linear-attn + full-attn, 64 layers, 1 MTP layer)
+- **Quantizer**: `nvidia-modelopt` 0.43.0 with `NVFP4_DEFAULT_CFG`
+- **Calibration**: 20 samples from `neuralmagic/calibration` (LLM split), max_seq_len 8192
+- **Ignored from quantization** (kept in bf16):
+  - `lm_head`
+  - All `model.visual.*` (vision tower) — then **physically deleted** in the text-only build
+  - All `*linear_attn.conv1d*` (Mamba-style SSM convolutions, 48 of the 64 layers)
+  - All `mtp.*` modules (the 1-layer MTP head: 15 tensors total, ~850 MB bf16)
+  - Other defaults from `NVFP4_DEFAULT_CFG`: `*router*`, `*mlp.gate.*`, `*block_sparse_moe.gate*`, `*output_layer*`
+
+## Usage with vLLM (Blackwell, SM120)
+
+### With MTP speculative decoding (recommended)
+
+```bash
+vllm serve sakamakismile/Qwen3.6-27B-Text-NVFP4-MTP \
+    --trust-remote-code \
+    --gpu-memory-utilization 0.85 \
+    --max-model-len 8192 \
+    --quantization modelopt \
+    --speculative-config '{"method":"qwen3_5_mtp","num_speculative_tokens":1}'
+```
+
+`num_speculative_tokens: 1` because the model has a single MTP layer (`mtp_num_hidden_layers=1`). The `qwen3_5_mtp` method handler is what vLLM uses for the Qwen3.5/3.6 family (internal `model_type: qwen3_5`); plain `mtp` also works as a fallback.
+
+### Without speculation
+
+```bash
+vllm serve sakamakismile/Qwen3.6-27B-Text-NVFP4-MTP \
+    --trust-remote-code \
+    --gpu-memory-utilization 0.85 \
+    --max-model-len 8192 \
+    --quantization modelopt
+```
+
+## Hardware target
+
+Built and tested on **NVIDIA RTX PRO 6000 Blackwell (SM120)**. Should also work on **RTX 5090** and other Blackwell consumer/workstation cards with sufficient VRAM (the model is roughly 14 GB after NVFP4 + ~850 MB of bf16 MTP/conv1d/lm_head).
+
+## Acknowledgements
+
+- [`osoleve`](https://huggingface.co/osoleve) — for the MTP-restoration recipe on Qwen3.5
+- [`Qwen`](https://huggingface.co/Qwen) — for the base model
+- [`nvidia-modelopt`](https://github.com/NVIDIA/TensorRT-Model-Optimizer) team
+- The reporters of Discussions #5 and #7 — for catching this cleanly
+
+## License
+
+Apache 2.0 (inherited from `Qwen/Qwen3.6-27B`).

chat_template.jinja

@@ -0,0 +1,154 @@
+{%- 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 %}
+{%- if tools and tools is iterable and tools is not mapping %}
+    {{- '<|im_start|>system\n' }}
+    {{- "# 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 %}
+        {{- '<|im_start|>system\n' + content + '<|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 %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- set reasoning_content = reasoning_content|trim %}
+        {%- if (preserve_thinking is defined and 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 %}
+                    {%- 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 +1,215 @@
+{
+  "architectures": [
+    "Qwen3_5ForConditionalGeneration"
+  ],
+  "dtype": "bfloat16",
+  "language_model_only": true,
+  "model_type": "qwen3_5",
+  "text_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_output_gate": true,
+    "bos_token_id": 248044,
+    "dtype": "bfloat16",
+    "eos_token_id": 248044,
+    "full_attention_interval": 4,
+    "head_dim": 256,
+    "hidden_act": "silu",
+    "hidden_size": 5120,
+    "initializer_range": 0.02,
+    "intermediate_size": 17408,
+    "layer_types": [
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention"
+    ],
+    "linear_conv_kernel_dim": 4,
+    "linear_key_head_dim": 128,
+    "linear_num_key_heads": 16,
+    "linear_num_value_heads": 48,
+    "linear_value_head_dim": 128,
+    "mamba_ssm_dtype": "float32",
+    "max_position_embeddings": 262144,
+    "model_type": "qwen3_5_text",
+    "mtp_num_hidden_layers": 1,
+    "mtp_use_dedicated_embeddings": false,
+    "num_attention_heads": 24,
+    "num_hidden_layers": 64,
+    "num_key_value_heads": 4,
+    "output_gate_type": "swish",
+    "pad_token_id": null,
+    "partial_rotary_factor": 0.25,
+    "rms_norm_eps": 1e-06,
+    "rope_parameters": {
+      "mrope_interleaved": true,
+      "mrope_section": [
+        11,
+        11,
+        10
+      ],
+      "partial_rotary_factor": 0.25,
+      "rope_theta": 10000000,
+      "rope_type": "default"
+    },
+    "tie_word_embeddings": false,
+    "use_cache": true,
+    "vocab_size": 248320
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.5.4",
+  "quantization_config": {
+    "config_groups": {
+      "group_0": {
+        "input_activations": {
+          "dynamic": false,
+          "num_bits": 4,
+          "type": "float",
+          "group_size": 16
+        },
+        "weights": {
+          "dynamic": false,
+          "num_bits": 4,
+          "type": "float",
+          "group_size": 16
+        },
+        "targets": [
+          "Linear"
+        ]
+      }
+    },
+    "ignore": [
+      "lm_head",
+      "model.language_model.layers.0.linear_attn.conv1d",
+      "model.language_model.layers.1.linear_attn.conv1d",
+      "model.language_model.layers.10.linear_attn.conv1d",
+      "model.language_model.layers.12.linear_attn.conv1d",
+      "model.language_model.layers.13.linear_attn.conv1d",
+      "model.language_model.layers.14.linear_attn.conv1d",
+      "model.language_model.layers.16.linear_attn.conv1d",
+      "model.language_model.layers.17.linear_attn.conv1d",
+      "model.language_model.layers.18.linear_attn.conv1d",
+      "model.language_model.layers.2.linear_attn.conv1d",
+      "model.language_model.layers.20.linear_attn.conv1d",
+      "model.language_model.layers.21.linear_attn.conv1d",
+      "model.language_model.layers.22.linear_attn.conv1d",
+      "model.language_model.layers.24.linear_attn.conv1d",
+      "model.language_model.layers.25.linear_attn.conv1d",
+      "model.language_model.layers.26.linear_attn.conv1d",
+      "model.language_model.layers.28.linear_attn.conv1d",
+      "model.language_model.layers.29.linear_attn.conv1d",
+      "model.language_model.layers.30.linear_attn.conv1d",
+      "model.language_model.layers.32.linear_attn.conv1d",
+      "model.language_model.layers.33.linear_attn.conv1d",
+      "model.language_model.layers.34.linear_attn.conv1d",
+      "model.language_model.layers.36.linear_attn.conv1d",
+      "model.language_model.layers.37.linear_attn.conv1d",
+      "model.language_model.layers.38.linear_attn.conv1d",
+      "model.language_model.layers.4.linear_attn.conv1d",
+      "model.language_model.layers.40.linear_attn.conv1d",
+      "model.language_model.layers.41.linear_attn.conv1d",
+      "model.language_model.layers.42.linear_attn.conv1d",
+      "model.language_model.layers.44.linear_attn.conv1d",
+      "model.language_model.layers.45.linear_attn.conv1d",
+      "model.language_model.layers.46.linear_attn.conv1d",
+      "model.language_model.layers.48.linear_attn.conv1d",
+      "model.language_model.layers.49.linear_attn.conv1d",
+      "model.language_model.layers.5.linear_attn.conv1d",
+      "model.language_model.layers.50.linear_attn.conv1d",
+      "model.language_model.layers.52.linear_attn.conv1d",
+      "model.language_model.layers.53.linear_attn.conv1d",
+      "model.language_model.layers.54.linear_attn.conv1d",
+      "model.language_model.layers.56.linear_attn.conv1d",
+      "model.language_model.layers.57.linear_attn.conv1d",
+      "model.language_model.layers.58.linear_attn.conv1d",
+      "model.language_model.layers.6.linear_attn.conv1d",
+      "model.language_model.layers.60.linear_attn.conv1d",
+      "model.language_model.layers.61.linear_attn.conv1d",
+      "model.language_model.layers.62.linear_attn.conv1d",
+      "model.language_model.layers.8.linear_attn.conv1d",
+      "model.language_model.layers.9.linear_attn.conv1d",
+      "model.visual*",
+      "mtp.fc",
+      "mtp.layers.0.input_layernorm",
+      "mtp.layers.0.mlp.down_proj",
+      "mtp.layers.0.mlp.gate_proj",
+      "mtp.layers.0.mlp.up_proj",
+      "mtp.layers.0.post_attention_layernorm",
+      "mtp.layers.0.self_attn.k_norm",
+      "mtp.layers.0.self_attn.k_proj",
+      "mtp.layers.0.self_attn.o_proj",
+      "mtp.layers.0.self_attn.q_norm",
+      "mtp.layers.0.self_attn.q_proj",
+      "mtp.layers.0.self_attn.v_proj",
+      "mtp.norm",
+      "mtp.pre_fc_norm_embedding",
+      "mtp.pre_fc_norm_hidden"
+    ],
+    "quant_algo": "NVFP4",
+    "producer": {
+      "name": "modelopt",
+      "version": "0.43.0"
+    },
+    "quant_method": "modelopt"
+  }
+}

generation_config.json

@@ -0,0 +1,13 @@
+{
+  "bos_token_id": 248044,
+  "do_sample": true,
+  "eos_token_id": [
+    248046,
+    248044
+  ],
+  "pad_token_id": 248044,
+  "temperature": 1.0,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "5.5.4"
+}

hf_quant_config.json

@@ -0,0 +1,63 @@
+{
+    "producer": {
+        "name": "modelopt",
+        "version": "0.43.0"
+    },
+    "quantization": {
+        "quant_algo": "NVFP4",
+        "kv_cache_quant_algo": null,
+        "group_size": 16,
+        "exclude_modules": [
+            "lm_head",
+            "model.language_model.layers.0.linear_attn.conv1d",
+            "model.language_model.layers.1.linear_attn.conv1d",
+            "model.language_model.layers.10.linear_attn.conv1d",
+            "model.language_model.layers.12.linear_attn.conv1d",
+            "model.language_model.layers.13.linear_attn.conv1d",
+            "model.language_model.layers.14.linear_attn.conv1d",
+            "model.language_model.layers.16.linear_attn.conv1d",
+            "model.language_model.layers.17.linear_attn.conv1d",
+            "model.language_model.layers.18.linear_attn.conv1d",
+            "model.language_model.layers.2.linear_attn.conv1d",
+            "model.language_model.layers.20.linear_attn.conv1d",
+            "model.language_model.layers.21.linear_attn.conv1d",
+            "model.language_model.layers.22.linear_attn.conv1d",
+            "model.language_model.layers.24.linear_attn.conv1d",
+            "model.language_model.layers.25.linear_attn.conv1d",
+            "model.language_model.layers.26.linear_attn.conv1d",
+            "model.language_model.layers.28.linear_attn.conv1d",
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