Squash history (storage cleanup); repository contents unchanged

Co-authored-by: jddqd <jddqd@users.noreply.huggingface.co>

.gitattributes

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README.md

@@ -0,0 +1,119 @@
+---
+base_model:
+- Qwen/Qwen3.5-2B
+language:
+- fr
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- french
+- conversational
+- edge
+- qwen
+license: apache-2.0
+datasets:
+- kurakurai/Luth-2-Post-Training-SFT
+- kurakurai/Luth-2-Post-Training-RL
+---
+
+![luth-2-banner](https://cdn-uploads.huggingface.co/production/uploads/66beff523ae330ae8b698ee9/wso_h0n6syZf9E8YDKWYA.png)
+
+# Luth-2-2B
+
+**Luth-2-2B** is a 1.88B-parameter (text only) non-reasoning model, setting a new **state of the art in French** for its size across math, code, instruction following, general knowledge and tool calling. It is trained on a 3B-token French SFT mixture followed by multi-domain on-policy distillation (MOPD). The model outperforms every other model in its size class on our selected French benchmarks and stays competitive with larger models. It is small enough for efficient local and on-device deployment.
+
+- 📄 **Blog**: [Luth-2: Pushing the French Capabilities of SLMs with MOPD](https://huggingface.co/blog/MaxLSB/luth-2)
+- 🤗 **Models**: [Luth-2-0.8B](https://huggingface.co/kurakurai/Luth-2-0.8B) · [Luth-2-2B](https://huggingface.co/kurakurai/Luth-2-2B)
+- 📊 **Datasets**: [SFT](https://huggingface.co/datasets/kurakurai/Luth-2-Post-Training-SFT) · [RL](https://huggingface.co/datasets/kurakurai/Luth-2-Post-Training-RL)
+- 💻 **Code**: [GitHub](https://github.com/kurakurai/Luth-2)
+- 🏆 **Leaderboard**: [French LLM Leaderboard](https://huggingface.co/spaces/kurakurai/llm_leaderboard_fr) 
+
+![luth2_benchmarks_2b_portrait](https://cdn-uploads.huggingface.co/production/uploads/noauth/a3vGEQW6ACZ2U2ni5KSdF.png)
+
+> [!NOTE]
+> **Luth-2-2B** inherits the VLM architecture of Qwen3.5-2B but was not trained on vision data. We do not recommend using it for vision tasks.
+
+## Model variants
+
+| Model | Description |
+|---|---|
+| [Luth-2-2B](https://huggingface.co/kurakurai/Luth-2-2B) | Original checkpoint in native format. Best for fine-tuning or inference with Transformers, vLLM and SGLang. |
+| [Luth-2-2B-GGUF](https://huggingface.co/kurakurai/Luth-2-2B-GGUF) | Quantized format for llama.cpp and compatible tools. Optimized for CPU inference and reduced memory usage. |
+
+## Training
+
+**Luth-2-2B** is post-trained from Qwen3.5-2B in two stages:
+
+1. **Supervised fine-tuning** on [Luth-2-Post-Training-SFT](https://huggingface.co/datasets/kurakurai/Luth-2-Post-Training-SFT), a 3B-token French mixture spanning math (37.2%), knowledge (27.9%), code (22.2%), instruction following (6.5%) and tool calling (6.3%). Prompts were translated from English SFT datasets and answers regenerated with strong open-source teachers.
+2. **Multi-domain on-policy distillation (MOPD)**. Three specialists (math, code, instruction following) are trained separately with GRPO on [Luth-2-Post-Training-RL](https://huggingface.co/datasets/kurakurai/Luth-2-Post-Training-RL), then distilled back into the SFT student.
+
+## Inference
+
+**Luth-2-2B** is supported by Transformers, vLLM, SGLang and more.
+
+Quick start with Transformers:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+model_id = "kurakurai/Luth-2-2B"
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    device_map="auto",
+    dtype="bfloat16",
+    # attn_implementation="flash_attention_2"  # uncomment on compatible GPU
+)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+prompt = "Quelle est la capitale de la France?"
+input_ids = tokenizer.apply_chat_template(
+    [{"role": "user", "content": prompt}],
+    add_generation_prompt=True,
+    return_tensors="pt",
+    tokenize=True,
+)["input_ids"].to(model.device)
+output = model.generate(
+    input_ids,
+    do_sample=True,
+    temperature=0.8,
+    top_p=0.95,
+    top_k=20,
+    max_new_tokens=512,
+    streamer=streamer,
+)
+```
+
+## Evaluation
+
+Evaluations can be reproduced using our [GitHub](https://github.com/kurakurai/Luth-2) repository. The benchmarks are French subsets or verified translations, scored with `temperature=0.6, top_p=0.95, top_k=20`, thinking disabled, averaged over 10 runs.
+
+| French Benchmarks | Luth-2-2B | Luth-1.7B-Instruct | Qwen3.5-2B |
+|---|--:|--:|--:|
+| MGSM-rev2 | **86.52** | 75.72 | 64.60 |
+| AIME 24 | **17.00** | 10.33 | 11.67 |
+| AIME 25 | **19.00** | 7.00 | 6.67 |
+| Math-500 | **81.52** | 65.26 | 65.06 |
+| Global-MMLU-Lite | **64.45** | 58.00 | 58.00 |
+| MMLU-ProX-Lite | **55.24** | 41.10 | 47.20 |
+| GPQA-Diamond | **41.97** | 30.20 | 36.80 |
+| IFEval | **75.06** | 64.47 | 61.91 |
+| Multi-IF | **69.67** | 46.05 | 45.38 |
+| HumanEval+ | **66.00** | 56.44 | 37.56 |
+| MBPP+ | **57.62** | 56.40 | 42.12 |
+| BFCL v2 | 68.91 | **71.05** | 51.78 |
+
+See the [French LLM Leaderboard](https://huggingface.co/spaces/kurakurai/llm_leaderboard_fr) for comparisons across models.
+
+## Contact
+
+Questions or feedback? Reach us on LinkedIn: [Maxence Lasbordes](https://www.linkedin.com/in/maxence-lasbordes/) and [Guillaume Pradel](https://www.linkedin.com/in/guillaume-pradel/).
+
+## Citation
+
+```bibtex
+@misc{luth2,
+  title  = {Luth-2: Pushing the French Capabilities of SLMs with MOPD},
+  author = {Maxence Lasbordes and Guillaume Pradel},
+  year   = {2026},
+  url    = {https://huggingface.co/MaxLSB/luth-2}
+}
+```

chat_template.jinja

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+{#- Qwen3.5's stock chat template, with {% generation %} markers so TRL's
+    assistant_only_loss can build the loss mask. Three deviations from stock:
+      - the assistant turn's opening tag and its <think> prefix stay OUTSIDE the
+        mask, because add_generation_prompt already emits them at inference time;
+      - the target — reasoning (if any), content, tool calls, <|im_end|> — is
+        wrapped in {% generation %};
+      - non-thinking is forced: the generation prompt always prefills a closed
+        '<think>\n\n</think>\n\n' and enable_thinking is ignored (see the end of
+        this file). Stock opens a bare '<think>\n' when enable_thinking is true.
+    Everything else, tool calling included, is byte-identical to stock. #}
+{%- 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 %}
+        {#- Emit the unmasked prefix (what add_generation_prompt would produce),
+            and defer the rest of the <think> block to the masked target. #}
+        {%- set target_prefix = '' %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if reasoning_content %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' }}
+                {%- set target_prefix = reasoning_content + '\n</think>\n\n' %}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n\n</think>\n\n' }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' }}
+        {%- endif %}
+        {%- generation %}
+        {{- target_prefix }}
+        {{- content }}
+        {%- 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 | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
+                        {{- args_value }}
+                        {{- '\n</parameter>\n' }}
+                    {%- endfor %}
+                {%- endif %}
+                {{- '</function>\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+        {%- endgeneration %}
+    {%- 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 %}
+{#- Non-thinking only: the think block is always prefilled closed. `enable_thinking` is ignored
+    (accepted, no effect) — this model was never tuned for thinking mode. #}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {{- '<think>\n\n</think>\n\n' }}
+{%- endif %}

config.json

@@ -0,0 +1,106 @@
+{
+  "architectures": [
+    "Qwen3_5ForConditionalGeneration"
+  ],
+  "dtype": "float32",
+  "eos_token_id": 248046,
+  "fp8": false,
+  "image_token_id": 248056,
+  "model_type": "qwen3_5",
+  "pad_token_id": 248044,
+  "text_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_output_gate": true,
+    "bos_token_id": null,
+    "dtype": "float32",
+    "eos_token_id": 248044,
+    "full_attention_interval": 4,
+    "head_dim": 256,
+    "hidden_act": "silu",
+    "hidden_size": 2048,
+    "initializer_range": 0.02,
+    "intermediate_size": 6144,
+    "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_conv_kernel_dim": 4,
+    "linear_key_head_dim": 128,
+    "linear_num_key_heads": 16,
+    "linear_num_value_heads": 16,
+    "linear_value_head_dim": 128,
+    "mamba_ssm_dtype": "float32",
+    "max_position_embeddings": 262144,
+    "mlp_only_layers": [],
+    "model_type": "qwen3_5_text",
+    "mtp_num_hidden_layers": 1,
+    "mtp_use_dedicated_embeddings": false,
+    "num_attention_heads": 8,
+    "num_hidden_layers": 24,
+    "num_key_value_heads": 2,
+    "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": true,
+    "use_cache": false,
+    "vocab_size": 248320
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.6.2",
+  "use_cache": false,
+  "use_grouped_mm": true,
+  "video_token_id": 248057,
+  "vision_config": {
+    "deepstack_visual_indexes": [],
+    "depth": 24,
+    "dtype": "float32",
+    "hidden_act": "gelu_pytorch_tanh",
+    "hidden_size": 1024,
+    "in_channels": 3,
+    "initializer_range": 0.02,
+    "intermediate_size": 4096,
+    "model_type": "qwen3_5_vision",
+    "num_heads": 16,
+    "num_position_embeddings": 2304,
+    "out_hidden_size": 2048,
+    "patch_size": 16,
+    "spatial_merge_size": 2,
+    "temporal_patch_size": 2
+  },
+  "vision_end_token_id": 248054,
+  "vision_start_token_id": 248053
+}

generation_config.json

@@ -0,0 +1,13 @@
+{
+  "do_sample": true,
+  "eos_token_id": [
+    248046,
+    248044
+  ],
+  "pad_token_id": 248044,
+  "temperature": 0.8,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "5.6.2",
+  "use_cache": true
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:de1af1d1c346231e6fc5ec1cd764b75d04fde30181cb066dd45168fa2d72dfa8
+size 4426558864

preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 16777216,
+        "shortest_edge": 65536
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "image_processor_type": "Qwen2VLImageProcessorFast"
+}

tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
+size 19989325

tokenizer_config.json

@@ -0,0 +1,32 @@
+{
+  "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",
+  "image_token": "<|image_pad|>",
+  "is_local": false,
+  "local_files_only": true,
+  "model_max_length": 262144,
+  "model_specific_special_tokens": {
+    "audio_bos_token": "<|audio_start|>",
+    "audio_eos_token": "<|audio_end|>",
+    "audio_token": "<|audio_pad|>",
+    "image_token": "<|image_pad|>",
+    "video_token": "<|video_pad|>",
+    "vision_bos_token": "<|vision_start|>",
+    "vision_eos_token": "<|vision_end|>"
+  },
+  "pad_token": "<|im_end|>",
+  "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+",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "video_token": "<|video_pad|>",
+  "vision_bos_token": "<|vision_start|>",
+  "vision_eos_token": "<|vision_end|>"
+}

video_preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 25165824,
+        "shortest_edge": 4096
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "video_processor_type": "Qwen3VLVideoProcessor"
+}