Upload folder using huggingface_hub

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@@ -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

CHECKSUMS.sha256

@@ -0,0 +1,6 @@
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+d511a969b32a16f1890326dadd4d04039779cebce7458b8e5d2ce7f3ce2550ed  model.safetensors.index.json

LICENSE

@@ -0,0 +1,233 @@
+Swift Open License v1.0
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+TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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+   Derivative of Qwen3.8-27B, Copyright 2026 Alibaba Cloud, Apache License 2.0.

LICENSE-APACHE-2.0

@@ -0,0 +1,202 @@
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+      any Contribution intentionally submitted for inclusion in the Work
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+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
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+   9. Accepting Warranty or Additional Liability. While redistributing
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+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
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+   limitations under the License.

NOTICE

@@ -0,0 +1,24 @@
+Swift 1.5 Qwen3.8-27B
+Copyright 2026 UkisAI
+
+UkisAI's contribution (the "Swift Contribution") is licensed under the
+Swift Open License v1.0. See LICENSE.
+
+This model is a Derivative Work of Qwen3.8-27B
+  https://huggingface.co/Qwen/Qwen3.8-27B
+  Copyright 2026 Alibaba Cloud
+  Licensed under the Apache License, Version 2.0. See LICENSE-APACHE-2.0.
+
+Swift 1.5 continues UkisAI's Swift 1.0 model, itself a Qwen3.8-27B
+derivative. The full release incorporates the Qwen3.8-27B Base Model and
+UkisAI's Swift 1.0 and Swift 1.5 contributions.
+
+Changes made by UkisAI (Apache License 2.0, Section 4(b) change notice):
+  - model-*.safetensors, model.safetensors.index.json: the model weights from
+    Swift 1.0 were further adapted by UkisAI using additional post-training
+    methods.
+  - README.md: replaced. LICENSE and NOTICE added.
+  - All other files (config.json, generation_config.json, chat_template.jinja,
+    tokenizer.json, tokenizer_config.json, vocab.json, merges.txt,
+    preprocessor_config.json, video_preprocessor_config.json) are retained from
+    the parent model and remain available under Apache License, Version 2.0.

README.md

@@ -0,0 +1,282 @@
+---
+license: other
+license_name: swift-open-license-1.0
+license_link: https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-27b/blob/main/LICENSE
+base_model: ukisai/Swift-1.5-Qwen3.8-27b
+base_model_relation: quantized
+library_name: transformers
+pipeline_tag: image-text-to-text
+language:
+- en
+- multilingual
+datasets:
+- HuggingFaceH4/ultrachat_200k
+tags:
+- gptq
+- int4
+- w4a16
+- 4-bit
+- quantized
+- vllm
+- intel-xpu
+- arc-pro-b70
+- mtp
+- speculative-decoding
+- gated-deltanet
+- qwen3_5
+- tool-calling
+---
+
+# Swift 1.5 Qwen3.8-27B — GPTQ INT4 (W4A16, group-128, symmetric) + BF16 MTP head
+
+Unofficial 4-bit GPTQ quantization of
+[`ukisai/Swift-1.5-Qwen3.8-27b`](https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-27b)
+for low-VRAM inference, with the MTP (multi-token-prediction) draft head and the
+vision tower deliberately **kept unquantized**. Produced with `gptqmodel 7.3.2`
+on an Intel Arc Pro B70 (30.3 GiB VRAM), ~2.4 h wall time. Quantization
+contract is identical to the Swift 1.0 artifact
+[`bjonor/Swift-Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16`](https://huggingface.co/bjonor/Swift-Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16).
+
+This model is **not affiliated with, endorsed by, or supported by UkisAI or
+Alibaba Cloud**. It is a community quantization; the licence terms of the base
+models below continue to apply (see [License](#license-and-attribution)).
+
+> **Runtime status (2026-09-25).** Verified on the stock
+> `vllm/vllm-openai-xpu:nightly` (`0.29.1rc1.dev422+gd05da62e9.xpu`,
+> `vllm-xpu-kernels 0.1.14.1`) with the two runtime patches from the recipe
+> repo: ready in 131 s, MTP-3 mean acceptance length 3.04 (68.0%), solo decode
+> 61.0 tok/s (p512/g128, median n=5), endpoint + streaming smoke test PASS.
+> `patch_mtp_boundary.py` is still required for requests that end exactly at
+> `--max-model-len`; mixed prefill + spec-decode batches run without the GDN
+> split-dispatch backport on this stack.
+
+## Model details
+
+| | |
+|---|---|
+| Base (fine-tune) | `ukisai/Swift-1.5-Qwen3.8-27b` (Swift Open License v1.0) |
+| Base (original) | `Qwen/Qwen3.8-27B` (Apache-2.0), Copyright 2026 Alibaba Cloud |
+| Architecture | `Qwen3_5ForConditionalGeneration`, 64 layers (hybrid Gated-DeltaNet linear attention + full attention every 4th layer), hidden 5120, 24 Q / 4 KV heads, head_dim 256, 248,320 vocab |
+| Quantization | GPTQ, 4-bit weights, 16-bit activations (W4A16), `group_size=128`, `sym=true`, `desc_act=false`, `lm_head` not quantized |
+| Preserved unquantized | 15 `mtp.*` tensors (BF16 draft head), 333 `model.visual.*` tensors |
+| Quantized modules | 400 (all linear projections of the 64 language layers) |
+| Checkpoint size | ~19 GB, 5 safetensors shards (2399 tensors) |
+| Native context | 262,144 tokens (validated serving up to 131,072) |
+| Quantizer | `gptqmodel 7.3.2` (torch 2.9.1+xpu) |
+| Source revision | `bc7a1e10b689648585a3ef41494c8d84cf77271a` |
+| Calibration | `HuggingFaceH4/ultrachat_200k` `train_sft[:256]`, truncated to 2048 tokens |
+| Calibration revision | `8049631c405ae6576f93f445c6b8166f76f5505a` |
+| Code | quantization, verification and Intel-XPU serving recipe: [BjornNordblom/intel-arc-b70-quant](https://github.com/BjornNordblom/intel-arc-b70-quant); serving patches from [SergiioB/intel-arc-pro-b70-inference-cookbook](https://github.com/SergiioB/intel-arc-pro-b70-inference-cookbook) |
+
+The `quantize_config.json` is field-for-field identical to the community
+reference artifact
+[`SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16`](https://huggingface.co/SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16)
+except for the quant-time-only `meta.offload_to_disk` flag. Note that the reference artifact
+quantizes the **base** Qwen3.8-27B; this repository quantizes the **Swift 1.5**
+fine-tune.
+
+## What was changed vs the source checkpoint
+
+- All linear projections of the language model → GPTQ INT4 (W4A16, g128, sym,
+  `desc_act=false`).
+- `mtp.*` draft tensors (15) and `model.visual.*` vision tensors (333) kept in
+  their original dtype; the `dynamic` exclusion `{"-:.*mtp.*": {}}` in
+  `quantize_config.json` records this.
+- Added: `quantize_config.json`, `quant_log.csv` (per-module quantization timings).
+- Unchanged: `config.json`, `generation_config.json`, `chat_template.jinja`,
+  `tokenizer.json`, `tokenizer_config.json`, `vocab.json`, `merges.txt`,
+  `processor_config.json`, `video_preprocessor_config.json`.
+- Added licence files: `LICENSE` (Swift Open License v1.0),
+  `LICENSE-APACHE-2.0`, `NOTICE`.
+
+## Quantization details
+
+| | |
+|---|---|
+| Method | GPTQ (gptqmodel 7.3.2), true-sequential, static groups off |
+| Bits / group | 4-bit / 128, symmetric, `desc_act=false` |
+| Damping | `damp_percent=0.05`, `damp_auto_increment=0.01`, Hessian staging FP32 |
+| Fallback | RTN for modules exceeding a 0.5% error threshold (none reported) |
+| Calibration | 256 UltraChat-SFT samples, ≤2048 tokens each |
+| Pack format | `int32`, `checkpoint_format=gptq`, `lm_head=false` |
+| Wall time | 2.38 h on one Arc Pro B70; host i9-13900K, 64 GB RAM |
+| Verification | contract check (`VERIFY PASS`), local serve + endpoint/streaming smoke test (`SMOKE PASS`) — see the GitHub repo |
+
+## How to use
+
+### vLLM (Intel XPU) — tested configuration
+
+`vllm/vllm-openai-xpu:nightly` (`0.29.1rc1.dev422+gd05da62e9.xpu`,
+`vllm-xpu-kernels 0.1.14.1`), with `patch_mtp_nightly.py` and
+`patch_mtp_boundary.py` applied at container start (`launch.sh` does this
+automatically):
+
+```bash
+vllm serve <this-repo> \
+  --quantization gptq --dtype float16 --max-model-len 131072 \
+  --gpu-memory-utilization 0.94 --kv-cache-dtype fp8 \
+  --max-num-seqs 2 --max-num-batched-tokens 8192 --enable-prefix-caching \
+  --speculative-config '{"method":"mtp","num_speculative_tokens":3}' \
+  --enable-auto-tool-choice --tool-call-parser qwen3_xml \
+  --language-model-only
+```
+
+Measured on this artifact: ready after 131 s, mean acceptance length 3.04
+(avg draft acceptance 68.0%), solo decode 61.0 tok/s median (n=5), short-prompt
+TTFT ~0.2 s, endpoint and streaming smoke tests pass. The pinned
+`vllm 0.27.2rc1.dev77+gac7509e2b.xpu` / `vllm-xpu-kernels 0.1.12.3` stack with
+the derived `vllm-xpu-gdn-split:0.1.12.3-p1` image also works
+(`--max-num-seqs 1`).
+
+Notes for this base model on XPU:
+
+- **MTP draft must be built unquantized.** The checkpoint flags this via the
+  `dynamic` exclusion; the runtime patch (or `B70_MTP_BF16_DRAFT=1`) enforces it
+  on XPU builds.
+- **`patch_mtp_boundary.py`.** With spec decoding enabled, an unpatched engine
+  dies when a request runs to exactly `--max-model-len`
+  (`EngineDeadError: Expected spec_token == num_spec_decodes *
+  (num_speculative_tokens + 1)` — the final draft group is truncated).
+- **Mixed-batch limitation (pinned stack only).** `vllm-xpu-kernels` < 0.1.14.1
+  abort the engine when speculative-decode tokens and prefill tokens land in the
+  same invocation. Use `--max-num-seqs 1`, kernels ≥ 0.1.14.1, or the Python
+  split-dispatch backport used by the pinned derived image. Not needed on the
+  nightly stack above.
+- `--kv-cache-dtype fp8` is a serving choice, not part of the checkpoint.
+
+Full reproduction path — pinned environments, `quant_swift.py` /
+`verify_quant.py`, `launch.sh` (MTP and vision flags), the XPU patches and the
+benchmark harness — is in the
+[recipe repository](https://github.com/BjornNordblom/intel-arc-b70-quant).
+
+### Transformers
+
+GPTQ checkpoints need a GPTQ-capable loader (`gptqmodel` or `auto-gptq`) and
+`transformers` ≥ 4.5x. The `mtp.*` tensors are not used by `transformers`
+inference and can be ignored.
+
+## Evaluation
+
+What was actually measured on this artifact (host: Arc Pro B70, vLLM XPU
+nightly, MTP 3 speculative tokens, fp8 KV cache, `--max-num-seqs 2`):
+
+| Check | Result |
+|---|---|
+| Quantization contract (`verify_quant.py`) | PASS — bits 4, group 128, sym, `desc_act=false`, 15 MTP tensors preserved, 333 vision tensors, 400 modules quantized, `lm_head` untouched |
+| Local serve + endpoint/streaming test (`test_serve.py`) | PASS (`SMOKE PASS`) |
+| Warm-up time to `/v1/models` | 131 s |
+| Decode, p512/g128, median of 5 | 61.0 tok/s (range 60.4–61.0) |
+| MTP draft acceptance | mean acceptance length 3.04, Avg draft acceptance 68.0% |
+| Solo TTFT (short prompt) | ~0.2–0.3 s |
+
+**No standard quality benchmarks (MMLU, GPQA, AIME, IFBench, perplexity) were
+run on this quantized artifact by the uploader**, and the concurrency harness
+(12-request storm / mixed batches) was validated on the Swift 1.0 artifact of
+the same architecture and contract, not re-run here. UkisAI publishes INT4
+W4A16 evaluations for the base model (GPQA-Diamond 88.38%, IFBench 71.25%,
+AIME 2026 84.00%) which are indicative but were measured on a different
+quantization pipeline. Treat accuracy figures as unverified for this artifact.
+
+## Intended use and out-of-scope
+
+- Intended: local inference and evaluation of the Swift 1.5 fine-tune on
+  Intel XPU / low-VRAM setups, including agent-style tool calling via
+  `qwen3_xml`.
+- Out of scope: any safety-critical, medical, legal, or production decision
+  making; anything requiring verified accuracy on this specific checkpoint;
+  vision/multimodal use — the vision tower is preserved but **was not validated**
+  (serving was tested language-only), and training data provenance is inherited
+  from the base models.
+- No safety alignment or red-teaming was performed by the uploader. Behavioural
+  risks of the base models (bias, hallucinations, prompt-injection
+  susceptibility) also apply here and may be amplified by quantization.
+
+## Limitations
+
+- Quantization is lossy; per-module error was not published beyond the RTN
+  fallback threshold report.
+- The MTP draft head only works in runtimes that can build it unquantized (see
+  above); otherwise disable speculative decoding.
+- Exporting to other formats (GGUF/AWQ) from this checkpoint is untested.
+- Multimodal inputs are structurally supported but untested.
+- Long-context behaviour was validated to 131,072 tokens, not to the native
+  262,144; the concurrency storm was not re-run on this artifact (see above).
+
+## Environmental impact
+
+One quantization run: ~2.4 h on a single Arc Pro B70 (230 W board power cap) —
+roughly **0.55 kWh** board energy, plus host overhead (i9-13900K, 64 GB RAM).
+Serving costs depend on runtime and context length.
+
+## License and attribution
+
+The following notice is required by the Swift Open License v1.0 for
+redistributors of quantizations/conversions/merges (verbatim from the base
+model's LICENSE appendix):
+
+> Copyright 2026 UkisAI. Swift Contribution licensed under the Swift Open
+> License v1.0 (https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-27b/blob/main/LICENSE).
+> Derivative of Qwen3.8-27B, Copyright 2026 Alibaba Cloud, Apache License 2.0.
+
+Included files: [`LICENSE`](LICENSE) (Swift Open License v1.0, governs the Swift
+Contribution), [`LICENSE-APACHE-2.0`](LICENSE-APACHE-2.0) (governs Qwen3.8-27B
+and the files unmodified from it), [`NOTICE`](NOTICE) (what UkisAI changed).
+
+Key terms to be aware of:
+
+- **Commercial-use threshold.** Personal, research, educational, evaluation and
+  commercial use are free for individuals and organisations with gross annual
+  revenue (including affiliates) up to **US$1,000,000**. Above that threshold,
+  commercial use of the Swift Contribution requires a separate Swift Enterprise
+  License from UkisAI. Nothing in the Swift Open License limits your rights in
+  Qwen3.8-27B itself, which remains Apache-2.0.
+- **No trademark rights.** The licence grants no rights to the "UkisAI" name or
+  marks; this card uses them only for attribution.
+- **Termination.** Non-compliance terminates the licence for the Swift
+  Contribution; rights in the base model under Apache-2.0 are unaffected.
+
+Addendum for this quantization (the uploader's modification notice):
+
+> GPTQ INT4 quantization of the Swift Contribution by Bjorn Nordblom, 2026,
+> distributed under the same Swift Open License v1.0 terms that apply to the
+> Swift Contribution. No additional rights are granted.
+
+## Citation
+
+```bibtex
+@misc{swift-1.5-qwen3.8-27b-gptq-int4,
+  title        = {Swift 1.5 Qwen3.8-27B GPTQ INT4 (W4A16, group-128, symmetric) with preserved BF16 MTP head},
+  author       = {Nordblom, Bjorn},
+  year         = {2026},
+  howpublished = {Hugging Face},
+  note         = {Quantization of ukisai/Swift-1.5-Qwen3.8-27b},
+}
+
+@misc{swift-1.5-qwen3.8-27b,
+  title  = {Swift 1.5 Qwen3.8-27B},
+  author = {UkisAI},
+  year   = {2026},
+  url    = {https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-27b}
+}
+
+@misc{qwen3.8-27b,
+  title  = {Qwen3.8-27B},
+  author = {Alibaba Cloud},
+  year   = {2026},
+  url    = {https://huggingface.co/Qwen/Qwen3.8-27B}
+}
+```
+
+## Acknowledgements
+
+- UkisAI for the Swift 1.5 fine-tune and the licence terms above.
+- Alibaba Cloud / Qwen for Qwen3.8-27B (Apache-2.0).
+- The `gptqmodel` project for the quantizer.
+- SergiioB's [intel-arc-pro-b70-inference-cookbook](https://github.com/SergiioB/intel-arc-pro-b70-inference-cookbook)
+  for the Intel Arc Pro B70 XPU serving patches (MTP BF16 draft, GDN boundary
+  handling, mixed-batch split-dispatch backport); the copies vendored in the
+  recipe repo are MIT, Copyright (c) 2026 SergiioB.
+
+## Model card contact
+
+Issues and questions: https://github.com/BjornNordblom/intel-arc-b70-quant/issues

chat_template.jinja

@@ -0,0 +1,170 @@
+{%- 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 +1,201 @@
+{
+  "architectures": [
+    "Qwen3_5ForConditionalGeneration"
+  ],
+  "dtype": "float16",
+  "image_token_id": 248056,
+  "language_model_only": false,
+  "model_type": "qwen3_5",
+  "quantization_config": {
+    "bits": 4,
+    "checkpoint_format": "gptq",
+    "desc_act": false,
+    "dynamic": {
+      "-:.*mtp.*": {}
+    },
+    "format": "gptq",
+    "group_size": 128,
+    "lm_head": false,
+    "meta": {
+      "act_group_aware": true,
+      "auto_forward_data_parallel": true,
+      "damp_auto_increment": 0.01,
+      "damp_percent": 0.05,
+      "dense_vram_strategy": "exclusive",
+      "dense_vram_strategy_devices": null,
+      "fallback": {
+        "smooth": null,
+        "strategy": "rtn",
+        "threshold": "0.5%"
+      },
+      "foem": null,
+      "gc_mode": "interval",
+      "gptaq": null,
+      "hessian": {
+        "chunk_bytes": null,
+        "chunk_size": null,
+        "staging_dtype": "float32"
+      },
+      "mock_quantization": false,
+      "moe_vram_strategy": "exclusive",
+      "moe_vram_strategy_devices": null,
+      "mse": 0.0,
+      "offload_to_disk": true,
+      "offload_to_disk_path": "/tmp/gptqmodel_71ep49kt",
+      "pack_impl": "cpu",
+      "quantizer": [
+        "gptqmodel:7.3.2"
+      ],
+      "static_groups": false,
+      "true_sequential": true,
+      "uri": "https://github.com/modelcloud/gptqmodel",
+      "wait_for_submodule_finalizers": false
+    },
+    "method": "gptq",
+    "pack_dtype": "int32",
+    "quant_method": "gptq",
+    "sym": true
+  },
+  "rope_parameters": {
+    "rope_theta": 10000.0,
+    "rope_type": "default"
+  },
+  "text_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_output_gate": true,
+    "bos_token_id": 248044,
+    "dtype": "float16",
+    "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",
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quantize_config.json

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+{
+  "bits": 4,
+  "dynamic": {
+    "-:.*mtp.*": {}
+  },
+  "group_size": 128,
+  "desc_act": false,
+  "lm_head": false,
+  "method": "gptq",
+  "quant_method": "gptq",
+  "format": "gptq",
+  "checkpoint_format": "gptq",
+  "pack_dtype": "int32",
+  "meta": {
+    "quantizer": [
+      "gptqmodel:7.3.2"
+    ],
+    "uri": "https://github.com/modelcloud/gptqmodel",
+    "damp_percent": 0.05,
+    "damp_auto_increment": 0.01,
+    "static_groups": false,
+    "true_sequential": true,
+    "mse": 0.0,
+    "gptaq": null,
+    "foem": null,
+    "act_group_aware": true,
+    "fallback": {
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+      "threshold": "0.5%",
+      "smooth": null
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+    "offload_to_disk": true,
+    "offload_to_disk_path": null,
+    "pack_impl": "cpu",
+    "gc_mode": "interval",
+    "wait_for_submodule_finalizers": false,
+    "auto_forward_data_parallel": true,
+    "dense_vram_strategy": "exclusive",
+    "dense_vram_strategy_devices": null,
+    "moe_vram_strategy": "exclusive",
+    "moe_vram_strategy_devices": null,
+    "mock_quantization": false,
+    "hessian": {
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+      "chunk_bytes": null,
+      "staging_dtype": "float32"
+    }
+  },
+  "sym": true
+}

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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+{
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+  "audio_bos_token": "<|audio_start|>",
+  "audio_eos_token": "<|audio_end|>",
+  "audio_token": "<|audio_pad|>",
+  "backend": "tokenizers",
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+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
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+  "local_files_only": false,
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+    "audio_token": "<|audio_pad|>",
+    "image_token": "<|image_pad|>",
+    "video_token": "<|video_pad|>",
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+  "processor_class": "Qwen3VLProcessor",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "video_token": "<|video_pad|>",
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+  "vision_eos_token": "<|vision_end|>"
+}

video_preprocessor_config.json

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