--- license: other license_name: qwen-research license_link: https://huggingface.co/Qwen/Qwen2.5-3B/blob/main/LICENSE language: - fr - en pipeline_tag: text-generation tags: - chat - qwen - qwen2.5 - finetune - french - english library_name: transformers inference: false model_creator: MaziyarPanahi quantized_by: MaziyarPanahi base_model: Qwen/Qwen2.5-3B model_name: calme-3.2-instruct-3b datasets: - MaziyarPanahi/french_instruct_sharegpt - arcee-ai/EvolKit-20k --- Calme-3 Models # MaziyarPanahi/calme-3.2-instruct-3b This model is an advanced iteration of the powerful `Qwen/Qwen2.5-3B`, specifically fine-tuned to enhance its capabilities in generic domains. # ⚡ Quantized GGUF All GGUF models are available here: [MaziyarPanahi/calme-3.2-instruct-3b-GGUF](https://huggingface.co/MaziyarPanahi/calme-3.2-instruct-3b-GGUF) # 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Leaderboard 2 coming soon! # Prompt Template This model uses `ChatML` prompt template: ``` <|im_start|>system {System} <|im_end|> <|im_start|>user {User} <|im_end|> <|im_start|>assistant {Assistant} ```` # How to use ```python # Use a pipeline as a high-level helper from transformers import pipeline messages = [ {"role": "user", "content": "Who are you?"}, ] pipe = pipeline("text-generation", model="MaziyarPanahi/calme-3.2-instruct-3b") pipe(messages) # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/calme-3.2-instruct-3b") model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/calme-3.2-instruct-3b") ``` # Ethical Considerations As with any large language model, users should be aware of potential biases and limitations. We recommend implementing appropriate safeguards and human oversight when deploying this model in production environments.