--- base_model: unsloth/gemma-1.1-2b-it-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - gemma - trl - sft --- ```python functions_metadata = [ { "type": "function", "function": { "name": "get_temperature", "description": "get temperature of a city", "parameters": { "type": "object", "properties": { "city": { "type": "string", "description": "name" } }, "required": [ "city" ] } } } ] messages = [ { "role": "user", "content": f"""Bạn là một trợ lý hữu ích có quyền truy cập vào các chức năng sau. Sử dụng chúng nếu cần -\n{str(functions_metadata)}"""}, { "role": "user", "content": "What is the temperature in Tokyo right now?"}, # You will get the previous prediction, extract it will the tag # execute the function and append it to the messages like below: { "role": "assistant", "content": """ {"name": "get_temperature", "arguments": '{"city": "Tokyo"}'} """}, { "role": "user", "content": """ {"temperature":30 C} """} ] input_ids = tokenizer.apply_chat_template( messages, add_generation_prompt=True, return_tensors="pt" ).to(model.device) outputs = model.generate( input_ids, max_new_tokens=256, do_sample=True, temperature=0.6, top_p=0.9, ) response = outputs[0][input_ids.shape[-1]:] print(tokenizer.decode(response, skip_special_tokens=True)) # >> The current temperature in Tokyo is 30 degrees Celsius. ``` # Uploaded model - **Developed by:** hiieu - **License:** apache-2.0 - **Finetuned from model :** unsloth/gemma-1.1-2b-it-bnb-4bit This gemma model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [](https://github.com/unslothai/unsloth)