Spaces:
Running
Running
File size: 880 Bytes
36781d0 e6e423f 36781d0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 |
import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer
# Load the model and tokenizer
model_name = "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
# Define the prediction function
def predict(input_text):
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
return response
# Create the Gradio interface
iface = gr.Interface(
fn=predict,
inputs=[gr.Textbox(lines=5, label="Input Text")],
outputs=[gr.Textbox(label="Generated Text")],
title="DeepSeek-R1-Distill-Qwen-1.5B Text Generation",
description="Enter text and the model will generate a continuation.",
)
if __name__ == "__main__":
iface.launch()
|