transformers safetensors mistral text-generation facebook meta pytorch llama llama-2 gguf function-calling function calling conversational arxiv:2310.06825 autotrain_compatible text-generation-inference endpoints_compatible region:us
{"architectures": ["MistralForCausalLM"], "model_type": "mistral", "tokenizer_config": {"bos_token": "<s>", "chat_template": "[INST] {% for message in messages %}{% if message['role'] == 'system' %}<<SYS>>\n{{ message['content'] }}\n<</SYS>>\n\n{% elif message['role'] == 'function_metadata' %}You have access to the following functions. Use them if required:\n\n{{ message['content'] }}\n\n{% elif message['role'] == 'user'  and loop.index0 == 1 %}{{ message['content'] }} [/INST]\n\n{% elif message['role'] == 'assistant' %}{{ message['content'] }}{{ eos_token }}{{ bos_token }}[INST] {% elif message['role'] == 'function_call' %}Function call: {{ message['content'] }}{{ eos_token }}{{ bos_token }}[INST] {% elif message['role'] == 'function_response' %}Here is the response to the function call. If helpful, use it to respond to my question:\n\n{{ message['content'] }} [/INST]\n\n{% elif message['role'] == 'user'  and loop.index0 != 1 %}{{ message['content'] }} [/INST]\n\n{% endif %}{% endfor %}", "eos_token": "</s>", "pad_token": "<unk>", "unk_token": "<unk>", "use_default_system_prompt": true}}