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README.md
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---
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base_model: microsoft/Phi-3-medium-4k-instruct
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language:
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- multilingual
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license: mit
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license_link: https://huggingface.co/microsoft/Phi-3-medium-4k-instruct/resolve/main/LICENSE
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pipeline_tag: text-generation
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tags:
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- nlp
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- code
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- openvino
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- nncf
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- 4-bit
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inference:
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parameters:
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temperature: 0.7
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widget:
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- messages:
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- role: user
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content: Can you provide ways to eat combinations of bananas and dragonfruits?
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---
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This model is a quantized version of [`microsoft/Phi-3-medium-4k-instruct`](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct) and is converted to the OpenVINO format. This model was obtained via the [nncf-quantization](https://huggingface.co/spaces/echarlaix/nncf-quantization) space with [optimum-intel](https://github.com/huggingface/optimum-intel).
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First make sure you have `optimum-intel` installed:
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```bash
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pip install optimum[openvino]
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```
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To load your model you can do as follows:
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```python
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from optimum.intel import OVModelForCausalLM
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model_id = "emmacall/Phi-3-medium-4k-instruct-openvino-4bit"
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model = OVModelForCausalLM.from_pretrained(model_id)
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```
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