This is a version of the original
Meta-Llama-3-8B-Instruct model converted to
OpenVINO™ IR (Intermediate Representation) format for optimized inference on Intel® hardware. The model is created using the examples shown in
OpenVINO™ Notebooks repository.
This model is designed for advanced natural language understanding and generation tasks, ideal for academic researchers and developers in commercial settings looking to integrate efficient AI capabilities into their applications. It is not to be used for creating or promoting harmful or illegal content as per the guidelines outlined in the
Meta Llama 3 Acceptable Use Policy.
This model is released under the Meta Llama 3 Community License. Redistribution requires inclusion of this license and a citation to the original model. Modifications and derivative works must prominently display "Built with Meta Llama 3" and adhere to the redistribution policies detailed in the original model
license terms.
For more information on the parameters, refer to the
OpenVINO™ 2024.1.0 documentationInstall packages required for using
Optimum Intel integration with the OpenVINO™ backend:
1from optimum.intel.openvino import OVModelForCausalLM
2from transformers import AutoTokenizer
3
4model_id = "nsbendre25/Llama-3-8B-Instruct-ov_fp16-int4_sym"
5
6# Initialize the tokenizer and model
7tokenizer = AutoTokenizer.from_pretrained(model_id)
8model = OVModelForCausalLM.from_pretrained(model_id)
9
10pipeline = transformers.pipeline("text-generation", model=model_id, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto")
11pipeline("i am in paris, plan me a 2 week trip")
