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Model: mamediarrafaye/qwen-senegal-generation
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+- fr
+- wo
+tags:
+- text-generation
+- senegal
+- wolof
+- french
+- code-switching
+- qwen
+- qwen2.5
+license: apache-2.0
+---
+
+# Qwen2.5-3B Sénégal Generation
+
+Modèle de génération de texte en **français sénégalais** avec code-switching Wolof-Français, spécialisé dans la conversation quotidienne sénégalaise.
+
+## Description
+
+Ce modèle est un fine-tuning de Qwen2.5-3B-Instruct sur un corpus de 9507 segments de français sénégalais authentique avec insertions naturelles de mots wolof. Il est spécialisé dans les conversations du quotidien : mobilité urbaine, mobile money, cybersécurité, vie universitaire sénégalaise, et interactions sociales au Sénégal.
+
+## Utilisation
+
+Le modèle suit le format Question/Réponse de son corpus d'entraînement :
+
+\`\`\`python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model = AutoModelForCausalLM.from_pretrained(
+    "mamediarrafaye/qwen-senegal-generation",
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+tokenizer = AutoTokenizer.from_pretrained(
+    "mamediarrafaye/qwen-senegal-generation"
+)
+
+def generer(message, max_new_tokens=150):
+    # Format obligatoire : Question/Réponse (format du corpus)
+    formatted = f"Question : {message}\nRéponse :"
+    
+    inputs = tokenizer(formatted, return_tensors="pt").to(model.device)
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=max_new_tokens,
+            temperature=0.7,
+            top_p=0.9,
+            do_sample=True,
+            repetition_penalty=1.2,
+            pad_token_id=tokenizer.eos_token_id,
+        )
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response.split("Réponse :")[-1].strip()
+
+## Domaines couverts
+
+- Vie universitaire sénégalaise (examens, mémoires, bourses, inscriptions)
+- Mobile money (Wave, Orange Money, transferts)
+- Cybersécurité et phishing
+- Transport urbain (BRT, Car Rapide, TER)
+- ASR et développement logiciel
+- Interactions sociales quotidiennes au Sénégal
+
+## Format d'entrée
+
+Le modèle attend le format suivant :
+\`\`\`
+Question : [votre message]
+Réponse :
+\`\`\`
+
+
+
+## Données
+
+- 9507 segments de français sénégalais authentique
+- 26% code-switching Wolof-Français
+- 74% français sénégalais standard
+- Sources : conversations simulées de contexte étudiant sénégalais
+
+## Entraînement
+
+- Modèle de base : Qwen2.5-3B-Instruct
+- Méthode : LoRA fine-tuning (r=64)
+- Epochs : 3
+- Learning rate : 2e-4
+- Framework : TRL/SFTTrainer
+
+## Exemples de sorties
+
+| Question | Réponse générée |
+|----------|----------------|
+| Gayi, qui a de la monnaie pour le taxi ? | Amoul problème, j'ai des billets cassés, je gère la course. |
+| Lu bess ? Le guichet automatique est en panne ? | Ah dédet, amoul solo, il y a juste une queue interminable dehors. |
+| Nanga def ? Les données sont bien anonymisées ? | Amoul problème, toutes les informations sensibles ont été effacées. |
+| Gayi, on fait la réunion à quelle heure ? | On se capte sur Google Meet vers 18h, le temps que tout le monde rentre. |
+
+## Limitations
+
+- Spécialisé dans les conversations du quotidien sénégalais — ne pas utiliser pour des questions générales hors domaine
+- Performances optimales avec le format Question/Réponse du corpus
+

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "float16",
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 32768,
+  "max_window_layers": 70,
+  "model_type": "qwen2",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 2,
+  "pad_token_id": null,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 1000000.0,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.12.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "repetition_penalty": 1.05,
+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "5.12.0"
+}

model.safetensors

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+size 6171926680

tokenizer.json

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+oid sha256:3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
+size 11421892

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "is_local": true,
+  "local_files_only": false,
+  "model_max_length": 131072,
+  "pad_token": "<|im_end|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}