| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| import torch | |
| pip install accelerate | |
| tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen1.5-1.8B", trust_remote_code=True) | |
| model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen1.5-1.8B", device_map="auto", trust_remote_code=True) | |
| def generate_text(prompt): | |
| inputs = tokenizer(prompt, return_tensors="pt").to(model.device) | |
| outputs = model.generate(**inputs, max_new_tokens=100) | |
| return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| gr.Interface(fn=generate_text, inputs="text", outputs="text", title="Qwen Text Generator").launch() | |