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