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Python chat_sample that supports most popular models like LLaMA 3

This example showcases inference of text-generation Large Language Models (LLMs): chatglm, LLaMA, Qwen and other models with the same signature. The application doesn't have many configuration options to encourage the reader to explore and modify the source code. For example, change the device for inference to GPU. The sample fearures openvino_genai.LLMPipeline and configures it for the chat scenario. There is also a Jupyter notebook which provides an example of LLM-powered Chatbot in Python.

Download and convert the model and tokenizers

The --upgrade-strategy eager option is needed to ensure optimum-intel is upgraded to the latest version.

It's not required to install ../../requirements.txt for deployment if the model has already been exported.

pip install --upgrade-strategy eager -r ../../requirements.txt
optimum-cli export openvino --trust-remote-code --model TinyLlama/TinyLlama-1.1B-Chat-v1.0 TinyLlama-1.1B-Chat-v1.0

Run:

chat_sample.py TinyLlama-1.1B-Chat-v1.0

To enable Unicode characters for Windows cmd open Region settings from Control panel. Administrative->Change system locale->Beta: Use Unicode UTF-8 for worldwide language support->OK. Reboot.

Discrete GPUs (dGPUs) usually provide better performance compared to CPUs. It is recommended to run larger models on a dGPU with 32GB+ RAM. For example, the model meta-llama/Llama-2-13b-chat-hf can benefit from being run on a dGPU. Modify the source code to change the device for inference to the GPU.

See https://github.com/openvinotoolkit/openvino.genai/blob/master/src/README.md#supported-models for the list of supported models.

Troubleshooting

Missing chat template

If you encounter an exception indicating a missing "chat template" when launching the ov::genai::LLMPipeline in chat mode, it likely means the model was not tuned for chat functionality. To work this around, manually add the chat template to tokenizer_config.json of your model. The following template can be used as a default, but it may not work properly with every model:

"chat_template": "{% for message in messages %}{% if (message['role'] == 'user') %}{{'<|im_start|>user\n' + message['content'] + '<|im_end|>\n<|im_start|>assistant\n'}}{% elif (message['role'] == 'assistant') %}{{message['content'] + '<|im_end|>\n'}}{% endif %}{% endfor %}",