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import gradio as gr
from transformers import pipeline
from huggingface_hub import get_hf_file_metadata, hf_hub_url, hub_hub_download
print(get_hf_file_metadata(hf_hub_url("eu-test/gpt2", "README.md")))
print(get_hf_file_metadata(hf_hub_url("eu-test/gpt2", "model.safetensors")))
hf_hub_download(repo_id="eu-test/gpt2", filename="64-8bits.tflite")
generator = pipeline('text-generation', model='eu-test/gpt2')
def generate(text):
result = generator(text, max_length=30, num_return_sequences=1)
return result[0]["generated_text"]
examples = [
["The Moon's orbit around Earth has"],
["The smooth Borealis basin in the Northern Hemisphere covers 40%"],
]
demo = gr.Interface(
fn=generate,
inputs=gr.inputs.Textbox(lines=5, label="Input Text"),
outputs=gr.outputs.Textbox(label="Generated Text"),
examples=examples
)
demo.launch()
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