| base_model: microsoft/Phi-3-medium-4k-instruct | |
| language: | |
| - multilingual | |
| license: mit | |
| license_link: https://huggingface.co/microsoft/Phi-3-medium-4k-instruct/resolve/main/LICENSE | |
| pipeline_tag: text-generation | |
| tags: | |
| - nlp | |
| - code | |
| - openvino | |
| - nncf | |
| - 4-bit | |
| inference: | |
| parameters: | |
| temperature: 0.7 | |
| widget: | |
| - messages: | |
| - role: user | |
| content: Can you provide ways to eat combinations of bananas and dragonfruits? | |
| 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). | |
| First make sure you have `optimum-intel` installed: | |
| ```bash | |
| pip install optimum[openvino] | |
| ``` | |
| To load your model you can do as follows: | |
| ```python | |
| from optimum.intel import OVModelForCausalLM | |
| model_id = "emmacall/Phi-3-medium-4k-instruct-openvino-4bit" | |
| model = OVModelForCausalLM.from_pretrained(model_id) | |
| ``` | |