--- base_model: microsoft/Phi-3.5-mini-instruct language: - multilingual library_name: transformers license: mit license_link: https://huggingface.co/microsoft/Phi-3.5-mini-instruct/resolve/main/LICENSE pipeline_tag: text-generation tags: - nlp - code - openvino - nncf - fp16 widget: - messages: - role: user content: Can you provide ways to eat combinations of bananas and dragonfruits? --- --- license: mit license_link: https://choosealicense.com/licenses/mit/ base_model: - microsoft/Phi-3.5-mini-instruct base_model_relation: optimized --- This model is a quantized version of [`microsoft/Phi-3.5-mini-instruct`](https://huggingface.co/microsoft/Phi-3.5-mini-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 = "AlexKoff88/Phi-3.5-mini-instruct-openvino-fp16" model = OVModelForCausalLM.from_pretrained(model_id) ```