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README.md
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# Mistral-7b-Instruct-v0.1-
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* Model creator: [Mistral AI](https://huggingface.co/mistralai)
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* Original model: [Mistral-7b-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)
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The provided OpenVINO™ IR model is compatible with:
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* OpenVINO version 2024.
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* Optimum Intel 1.16.0 and higher
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## Running Model Inference
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1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
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from transformers import AutoTokenizer
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from optimum.intel.openvino import OVModelForCausalLM
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model_id = "OpenVINO/mistral-7b-instrcut-v0.1-
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = OVModelForCausalLM.from_pretrained(model_id)
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messages = [
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{"role": "user", "content": "What is your favourite condiment?"},
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{"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"},
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{"role": "user", "content": "Do you have mayonnaise recipes?"}
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]
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inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
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outputs = model.generate(inputs, max_new_tokens=20)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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# Mistral-7b-Instruct-v0.1-int4-ov
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* Model creator: [Mistral AI](https://huggingface.co/mistralai)
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* Original model: [Mistral-7b-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)
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The provided OpenVINO™ IR model is compatible with:
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* OpenVINO version 2024.2.0 and higher
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* Optimum Intel 1.16.0 and higher
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## Running Model Inference with [Optimum Intel](https://huggingface.co/docs/optimum/intel/index)
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1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
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from transformers import AutoTokenizer
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from optimum.intel.openvino import OVModelForCausalLM
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model_id = "OpenVINO/mistral-7b-instrcut-v0.1-int4-ov"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = OVModelForCausalLM.from_pretrained(model_id)
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inputs = tokenizer("What is OpenVINO?", return_tensors="pt")
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outputs = model.generate(inputs, max_new_tokens=20)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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