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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() |