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--- |
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license: apache-2.0 |
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language: |
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- en |
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--- |
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# Mistral-7b-Instruct-v0.1-int8-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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## Description |
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This is [Mistral-7b-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT8 by [NNCF](https://github.com/openvinotoolkit/nncf). |
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## Quantization Parameters |
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Weight compression was performed using `nncf.compress_weights` with the following parameters: |
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* mode: **INT8_ASYM** |
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For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/2024/openvino-workflow/model-optimization-guide/weight-compression.html) |
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## Compatibility |
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The provided OpenVINO™ IR model is compatible with: |
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* OpenVINO version 2024.1.0 and higher |
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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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``` |
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pip install optimum[openvino] |
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``` |
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2. Run model inference: |
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``` |
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from transformers import AutoTokenizer |
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from optimum.intel.openvino import OVModelForCausalLM |
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model_id = "OepnVINO/mistral-7b-instrcut-v0.1-int8-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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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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``` |
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For more examples and possible optimizations, refer to the [OpenVINO Large Language Model Inference Guide](https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide.html). |
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## Limitations |
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Check the original model card for [limitations](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1#limitations). |
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## Legal information |
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The original model is distributed under [Apache 2.0](https://choosealicense.com/licenses/apache-2.0/) license. More details can be found in [original model card](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1). |
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## Disclaimer |
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Intel is committed to respecting human rights and avoiding causing or contributing to adverse impacts on human rights. See [Intel’s Global Human Rights Principles](https://www.intel.com/content/dam/www/central-libraries/us/en/documents/policy-human-rights.pdf). Intel’s products and software are intended only to be used in applications that do not cause or contribute to adverse impacts on human rights. |
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