---
library_name: transformers
language:
- en
license: apache-2.0
---

## Virtual Cleint
<p align="center">
  <img src="client.png" alt="client" width="400"/>
</p>

### 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
![dataset](dataset.png)


## 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**.