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README.md

@@ -0,0 +1,123 @@
+---
+base_model:
+- Qwen/Qwen3.5-0.8B
+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-2-0.8B
+
+**Luth-2-0.8B** is a 750M-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 models 2 to 3 times larger. 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_0.8b_portrait](https://cdn-uploads.huggingface.co/production/uploads/66beff523ae330ae8b698ee9/gER5neg6becY6FxAeXFSG.png)
+
+> [!NOTE]
+> **Luth-2-0.8B** inherits the VLM architecture of Qwen3.5-0.8B but was not trained on vision data. We do not recommend using it for vision tasks.
+
+## Model variants
+
+| Model | Description |
+|---|---|
+| [Luth-2-0.8B](https://huggingface.co/kurakurai/Luth-2-0.8B) | Original checkpoint in native format. Best for fine-tuning or inference with Transformers, vLLM and SGLang. |
+| [Luth-2-0.8B-GGUF](https://huggingface.co/kurakurai/Luth-2-0.8B-GGUF) | Quantized format for llama.cpp and compatible tools. Optimized for CPU inference and reduced memory usage. |
+
+## Training
+
+**Luth-2-0.8B** is post-trained from Qwen3.5-0.8B 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-2-0.8B** is supported by Transformers, vLLM, SGLang and more.
+
+Quick start with Transformers:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+
+model_id = "kurakurai/Luth-2-0.8B"
+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-2-0.8B | Luth-0.6B-Instruct | Qwen3.5-0.8B |
+|---|--:|--:|--:|
+| MGSM-rev2 | **72.92** | 58.52 | 35.20 |
+| AIME 24 | **5.67** | 2.00 | 1.00 |
+| AIME 25 | **8.67** | 1.33 | 0.33 |
+| Math-500 | **57.60** | 44.74 | 27.46 |
+| Global-MMLU-Lite | **53.30** | 40.20 | 44.00 |
+| MMLU-ProX-Lite | **38.93** | 25.40 | 27.60 |
+| GPQA-Diamond | **26.87** | 25.60 | 23.80 |
+| IFEval | **71.23** | 51.23 | 44.47 |
+| Multi-IF | **61.52** | 33.77 | 32.72 |
+| HumanEval+ | **46.81** | 30.25 | 10.87 |
+| MBPP+ | **42.33** | 34.74 | 18.20 |
+| BFCL v2 | **64.02** | 61.72 | 51.49 |
+
+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

@@ -0,0 +1,174 @@
+{#- 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": 1024,
+    "initializer_range": 0.02,
+    "intermediate_size": 3584,
+    "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": 12,
+    "dtype": "float32",
+    "hidden_act": "gelu_pytorch_tanh",
+    "hidden_size": 768,
+    "in_channels": 3,
+    "initializer_range": 0.02,
+    "intermediate_size": 3072,
+    "model_type": "qwen3_5_vision",
+    "num_heads": 12,
+    "num_position_embeddings": 2304,
+    "out_hidden_size": 1024,
+    "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 sha256:24522cd21e3d48a6699fd00f6f65cbd5af6b9a2a98acddd1068f18715d80a27d
+size 1706030528

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": false,
+  "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"
+}