| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| import torch | |
| model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-llm-7b-chat", device_map="auto", torch_dtype=torch.float16) | |
| tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-llm-7b-chat") | |
| def chat(prompt): | |
| inputs = tokenizer(prompt, return_tensors="pt").to(model.device) | |
| outputs = model.generate(**inputs, max_new_tokens=256, do_sample=True) | |
| return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| gr.Interface(fn=chat, inputs="text", outputs="text").launch() |