--- base_model: - mistralai/Ministral-8B-Instruct-2410 language: - en - fr - de - es - it - pt - zh - ja - ru - ko license: other license_name: mrl license_link: https://mistral.ai/licenses/MRL-0.1.md inference: false --- # Ministral-8B-Instruct-2410-HF ## Model Description Ministral-8B-Instruct-2410-HF is the Hugging Face version of Ministral-8B-Instruct-2410 by Mistral AI. It is a multilingual instruction-tuned language model based on the Mistral architecture, designed for various natural language processing tasks with a focus on chat-based interactions. ## Installation To use this model, install the required packages: ```bash pip install -U transformers ``` ## Usage Example Here's a Python script demonstrating how to use the model for chat completion: ```python from transformers import AutoModelForCausalLM, AutoTokenizer # Model setup model_name = "prince-canuma/Ministral-8B-Instruct-2410-HF" model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto") tokenizer = AutoTokenizer.from_pretrained(model_name) # Chat interaction prompt = "Tell me a short story about a robot learning to paint." messages = [{"role": "user", "content": prompt}] text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) input_ids = tokenizer(text, return_tensors="pt").to(model.device) # Generate response output = model.generate(**input_ids, max_new_tokens=500, temperature=0.7, do_sample=True) response = tokenizer.decode(output[0][input_ids.input_ids.shape[1]:]) print("User:", prompt) print("Model:", response) ``` ## Model Details - **Developed by:** Mistral AI - **Model type:** Causal Language Model - **Language(s):** English - **License:** [mrl](https://mistral.ai/licenses/MRL-0.1.md) - **Resources for more information:** - [Model Repository](https://huggingface.co/prince-canuma/Ministral-8B-Instruct-2410-HF) - [Mistral AI GitHub](https://github.com/mistralai)