File size: 1,446 Bytes
722177d 8fe6ab2 921a7bd 722177d 921a7bd 3aaf394 19e4851 921a7bd 80ca826 626064c 921a7bd 626064c 921a7bd 19e4851 921a7bd 626064c |
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 28 29 30 31 32 33 34 35 36 37 38 39 40 |
import gradio as gr
import spaces
from transformers import AutoModelForCausalLM, AutoTokenizer
# Load model and tokenizer
model_name = "infly/OpenCoder-8B-Instruct"
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
@spaces.GPU
def generate_text(prompt):
inputs = tokenizer(prompt, return_tensors="pt", truncation=True, padding=True)
outputs = model.generate(inputs["input_ids"], max_length=100, num_return_sequences=1)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
iface = gr.Interface(
fn=generate_text,
inputs=[
gr.Textbox(label="Enter your prompt", placeholder="Start typing...", lines=5),
gr.Slider(minimum=50, maximum=200, value=100, step=1, label="Max Length"),
gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.1, label="Temperature"),
],
outputs="text",
title="OpenCoder 8B Instruct",
description="Generate text using the OpenCoder model. Adjust the settings and input a prompt to generate responses.",
)
# Launch the Gradio app
iface.launch(share=True)
# Create Gradio interface
# interface = gr.Interface(
# fn=generate_text,
# inputs=gr.Textbox(lines=2, placeholder="Enter your prompt here..."),
# outputs=gr.Textbox(label="Generated Text")
# )
# # Launch the Gradio app
# if __name__ == "__main__":
# interface.launch() |