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