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Model: mamediarrafaye/qwen-senegal-generation Source: Original Platform
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README.md
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README.md
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---
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language:
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- fr
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- wo
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tags:
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- text-generation
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- senegal
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- wolof
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- french
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- code-switching
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- qwen
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- qwen2.5
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license: apache-2.0
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---
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# Qwen2.5-3B Sénégal Generation
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Modèle de génération de texte en **français sénégalais** avec code-switching Wolof-Français, spécialisé dans la conversation quotidienne sénégalaise.
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## Description
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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.
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## Utilisation
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Le modèle suit le format Question/Réponse de son corpus d'entraînement :
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\`\`\`python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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model = AutoModelForCausalLM.from_pretrained(
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"mamediarrafaye/qwen-senegal-generation",
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torch_dtype=torch.float16,
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device_map="auto",
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)
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tokenizer = AutoTokenizer.from_pretrained(
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"mamediarrafaye/qwen-senegal-generation"
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)
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def generer(message, max_new_tokens=150):
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# Format obligatoire : Question/Réponse (format du corpus)
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formatted = f"Question : {message}\nRéponse :"
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inputs = tokenizer(formatted, return_tensors="pt").to(model.device)
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with torch.no_grad():
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outputs = model.generate(
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**inputs,
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max_new_tokens=max_new_tokens,
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temperature=0.7,
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top_p=0.9,
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do_sample=True,
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repetition_penalty=1.2,
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pad_token_id=tokenizer.eos_token_id,
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)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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return response.split("Réponse :")[-1].strip()
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## Domaines couverts
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- Vie universitaire sénégalaise (examens, mémoires, bourses, inscriptions)
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- Mobile money (Wave, Orange Money, transferts)
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- Cybersécurité et phishing
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- Transport urbain (BRT, Car Rapide, TER)
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- ASR et développement logiciel
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- Interactions sociales quotidiennes au Sénégal
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## Format d'entrée
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Le modèle attend le format suivant :
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\`\`\`
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Question : [votre message]
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Réponse :
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\`\`\`
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## Données
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- 9507 segments de français sénégalais authentique
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- 26% code-switching Wolof-Français
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- 74% français sénégalais standard
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- Sources : conversations simulées de contexte étudiant sénégalais
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## Entraînement
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- Modèle de base : Qwen2.5-3B-Instruct
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- Méthode : LoRA fine-tuning (r=64)
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- Epochs : 3
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- Learning rate : 2e-4
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- Framework : TRL/SFTTrainer
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## Exemples de sorties
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| Question | Réponse générée |
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|----------|----------------|
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| Gayi, qui a de la monnaie pour le taxi ? | Amoul problème, j'ai des billets cassés, je gère la course. |
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| Lu bess ? Le guichet automatique est en panne ? | Ah dédet, amoul solo, il y a juste une queue interminable dehors. |
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| Nanga def ? Les données sont bien anonymisées ? | Amoul problème, toutes les informations sensibles ont été effacées. |
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| Gayi, on fait la réunion à quelle heure ? | On se capte sur Google Meet vers 18h, le temps que tout le monde rentre. |
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## Limitations
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- Spécialisé dans les conversations du quotidien sénégalais — ne pas utiliser pour des questions générales hors domaine
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- Performances optimales avec le format Question/Réponse du corpus
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54
chat_template.jinja
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
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{{- messages[0]['content'] }}
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{%- else %}
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
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{{- "\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>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\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" }}
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{%- else %}
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{%- if messages[0]['role'] == 'system' %}
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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69
config.json
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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"dtype": "float16",
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"eos_token_id": 151645,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 11008,
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"layer_types": [
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"full_attention",
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],
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"max_position_embeddings": 32768,
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"max_window_layers": 70,
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"model_type": "qwen2",
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"num_attention_heads": 16,
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"num_hidden_layers": 36,
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"num_key_value_heads": 2,
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"pad_token_id": null,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_type": "default"
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},
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"sliding_window": null,
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"tie_word_embeddings": true,
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"transformers_version": "5.12.0",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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generation_config.json
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generation_config.json
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{
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"repetition_penalty": 1.05,
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"temperature": 0.7,
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"top_k": 20,
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"top_p": 0.8,
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"transformers_version": "5.12.0"
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}
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model.safetensors
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size 6171926680
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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size 11421892
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tokenizer_config.json
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tokenizer_config.json
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"is_local": true,
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"pad_token": "<|im_end|>",
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"unk_token": null
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}
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