inference card added
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README.md
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This is the 8-bit quantized model of the [ministral-8B](https://huggingface.co/mistralai/Ministral-8B-Instruct-2410) by Mistral-AI.Please follow the following instruction to run the model on your device:
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There are multiple ways to infer the model. Firstly, let's install `llama.cpp` and use it for the inference:
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1. Install
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```
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git clone https://github.com/ggerganov/llama.cpp
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!mkdir llama.cpp/build && cd llama.cpp/build && cmake .. && cmake --build . --config Release
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```
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2. Inference
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```
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./llama.cpp/build/bin/llama-cli -m ./ministral-8b_Q8_0.gguf -cnv -p "You are a helpful assistant"
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```
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Here, you can interact with model from your terminal.
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**Alternatively**, we can use python binding of the `llama.cpp` to run the model on both CPU and GPU.
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1. Install
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```
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pip install --no-cache-dir llama-cpp-python==0.2.85 --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu122
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```
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2. Inference on CPU
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```
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from llama_cpp import Llama
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model_path = "./ministral-8b_Q8_0.gguf"
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llm = Llama(model_path=model_path, n_threads=8, verbose=False)
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prompt = "What should I do when my eyes are dry?"
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output = llm(
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prompt=f"<|user|>\n{prompt}<|end|>\n<|assistant|>",
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max_tokens=4096,
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stop=["<|end|>"],
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echo=False, # Whether to echo the prompt
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)
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print(output)
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```
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3. Inference on GPU
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```
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from llama_cpp import Llama
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model_path = "./ministral-8b_Q8_0.gguf"
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llm = Llama(model_path=model_path, n_threads=8, n_gpu_layers=-1, verbose=False)
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prompt = "What should I do when my eyes are dry?"
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output = llm(
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prompt=f"<|user|>\n{prompt}<|end|>\n<|assistant|>",
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max_tokens=4096,
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stop=["<|end|>"],
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echo=False, # Whether to echo the prompt
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)
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print(output)
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```
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