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import gradio as gr | |
from thirdai import bolt, licensing | |
from transformers import GPT2Tokenizer | |
licensing.activate("7511CC-0E24D7-69439D-5D6CBA-33AAFD-V3") | |
tokenizer = GPT2Tokenizer.from_pretrained("gpt2") | |
model = bolt.GenerativeModel.load("./generative.model") | |
def generate(prompt): | |
prompt = tokenizer.encode(prompt) | |
stream = model.streaming_generation( | |
input_tokens=prompt, | |
prediction_chunk_size=2, | |
max_predictions=100, | |
beam_width=10, | |
) | |
for res in stream: | |
yield tokenizer.decode(res) | |
with gr.Blocks() as demo: | |
output = gr.TextArea(label="Output") | |
prompt = gr.Textbox( | |
label="Prompt", | |
) | |
prompt.submit(generate, inputs=[prompt], outputs=[output]) | |
btn = gr.Button(value="Generate") | |
btn.click(generate, inputs=[prompt], outputs=[output]) | |
gr.ClearButton(components=[prompt, output]) | |
if __name__ == "__main__": | |
demo.queue() | |
demo.launch() | |