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README.md
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# Mixtral-8x7b-Instruct-v0.1-int4-ov
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* Model creator: [Mistral AI](https://huggingface.co/mistralai)
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* Original model: [Mixtral 8X7B Instruct v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)
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## Description
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This is [Mixtral-8x7b-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) model converted to [OpenVINO](https://docs.openvino.ai/2024/home.html) Intermediate Representation (IR) format with INT4 compressed weights using [NNCF](https://github.com/openvinotoolkit/nncf).
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* mode: **INT4_SYM**
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* group_size: **128**
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* ratio: **0.8**
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## Compatibility
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##
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To install the required components for using [Optimum Intel integration](https://huggingface.co/docs/optimum/intel/index) with the OpenVINO backend, do:
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```
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pip install optimum[openvino]
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```
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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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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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For more examples and possible optimizations
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language:
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---
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# Mixtral-8x7b-Instruct-v0.1-int4-ov
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* Model creator: [Mistral AI](https://huggingface.co/mistralai)
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* Original model: [Mixtral 8X7B Instruct v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)
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## Description
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This is [Mixtral-8x7b-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-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 INT4 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: **INT4_SYM**
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* group_size: **128**
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* ratio: **0.8**
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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 2024.0.0 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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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/Mixtral-8x7B-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/Mixtral-8x7B-Instruct-v0.1).
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