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--- |
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library_name: transformers |
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language: |
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- en |
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license: apache-2.0 |
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--- |
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## Virtual Cleint |
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<p align="center"> |
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<img src="client.png" alt="client" width="400"/> |
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</p> |
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### example |
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``` |
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import torch |
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from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer |
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MODEL_ID = "jaeyong2/Virtual-Client-Preview" |
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torch_dtype = torch.bfloat16 if torch.cuda.is_available() else torch.float32 |
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tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, use_fast=True) |
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model = AutoModelForCausalLM.from_pretrained( |
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MODEL_ID, |
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torch_dtype=torch_dtype, |
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device_map="auto", |
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) |
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persona = "Pilates trainer with extensive gym experience" |
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messages = [ |
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{"role": "system", "content": "You are a question-generating AI that receives personas from users and generates the most appropriate questions"}, |
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{"role": "user", "content": persona} |
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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(model.device) |
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generated_ids = model.generate( |
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**model_inputs, |
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max_new_tokens=512 |
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) |
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generated_ids = [ |
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) |
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] |
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] |
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``` |
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### result |
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``` |
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What are some of the key principles you follow when designing a new workout program? |
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``` |
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### How to make dataset |
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## License |
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- Qwen/Qwen2.5-1.5B-Instruct : https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct/blob/main/LICENSE |
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## Acknowledgement |
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This research is supported by **TPU Research Cloud program**. |
