|
|
import gradio as gr |
|
|
from transformers import AutoModelForCausalLM, AutoTokenizer |
|
|
|
|
|
|
|
|
model_name = "csdnkey/fortune_tellingb_1.5" |
|
|
tokenizer = AutoTokenizer.from_pretrained(model_name) |
|
|
model = AutoModelForCausalLM.from_pretrained(model_name) |
|
|
|
|
|
def generate_text(input_text): |
|
|
inputs = tokenizer(input_text, return_tensors="pt") |
|
|
outputs = model.generate(**inputs, max_length=100) |
|
|
return tokenizer.decode(outputs[0], skip_special_tokens=True) |
|
|
|
|
|
|
|
|
demo = gr.Interface( |
|
|
fn=generate_text, |
|
|
inputs="text", |
|
|
outputs="text", |
|
|
title="你的模型名称", |
|
|
description="使用你的模型进行文本生成" |
|
|
) |
|
|
demo.launch() |