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--- |
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language: |
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- en |
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- vi |
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pipeline_tag: text-generation |
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tags: |
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- chat |
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library_name: transformers |
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license: apache-2.0 |
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datasets: |
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- thanghf/demo_math |
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--- |
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## Quick Start |
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### 🤗 Hugging Face Transformers |
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Here we show a code snippet to show you how to use the chat model with `transformers`: |
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```python |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer |
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model = AutoModelForCausalLM.from_pretrained("thanghf/demo_math_model",torch_dtype=torch.bfloat16,device_map='auto') |
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tokenizer = AutoTokenizer.from_pretrained("thanghf/demo_math_model") |
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model.eval() |
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streamer = TextStreamer(tokenizer) |
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prompt = """Gieo hai con súc xắc cân đối và đồng chất. Xác suất để tổng số chấm trên mặt xuất hiện của hai con súc xắc bằng 7 là:""" |
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messages = [ |
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{"role": "system", "content": "Please reason step by step, and put your final answer within \\boxed{}."}, |
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{"role": "user", "content": prompt} |
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] |
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text = tokenizer.apply_chat_template( |
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messages, |
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tokenize=False, |
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add_generation_prompt=True |
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) |
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model_inputs = tokenizer([text], return_tensors="pt").to(device) |
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generated_ids = model.generate( |
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**model_inputs, |
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max_new_tokens=4096, |
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streamer=streamer |
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) |
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``` |
