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import gradio as gr | |
from transformers import AutoTokenizer, AutoModelForCausalLM | |
model_name = "cognitivecomputations/dolphin-2.8-mistral-7b-v02" | |
tokenizer = AutoTokenizer.from_pretrained(model_name) | |
model = AutoModelForCausalLM.from_pretrained(model_name) | |
def generate_text(prompt): | |
inputs = tokenizer(prompt, return_tensors="pt") | |
outputs = model.generate(**inputs, max_length=200) | |
return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
iface = gr.Interface( | |
fn=generate_text, | |
inputs="text", | |
outputs="text", | |
title="Dolphin Mistral Demo", | |
description="Enter a prompt and get a generated response." | |
) | |
iface.launch() |