| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| def generate_response(input_text): | |
| model_name = "cognitivecomputations/dolphin-2.1-mistral-7b" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForSeq2SeqLM.from_pretrained(model_name) | |
| inputs = tokenizer(input_text, return_tensors="pt") | |
| outputs = model.generate(**inputs, max_length=200, num_beams=5, early_stopping=True) | |
| response = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| return response | |
| iface = gr.Interface(fn=generate_response, inputs="text", outputs="text") | |
| iface.launch() |