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| #TODO: set seed and argument for it | |
| #TODO: use transformer library directly | |
| import gradio as gr | |
| from gradio import mix | |
| from transformers import pipeline, set_seed | |
| #title = "trustworthy artificial intelligence workshop - content generator" | |
| description = "based on the gpt2 demo interface by <a href='https://huggingface.co/spaces/docs-demos/gpt2/tree/main'>ahsen khaliq</a>" | |
| #io1 = gr.Interface.load("huggingface/distilgpt2") | |
| generator = pipeline('text-generation', model='gpt2') | |
| set_seed(42) | |
| io2 = gr.Interface.load("huggingface/gpt2-large") | |
| #io3 = gr.Interface.load("huggingface/gpt2-medium") | |
| #io4 = gr.Interface.load("huggingface/gpt2-xl") | |
| def inference(text): | |
| """ | |
| if model == "gpt2-large": | |
| outtext = io2(text) | |
| elif model == "gpt2-medium": | |
| outtext = io3(text) | |
| elif model == "gpt2-xl": | |
| outtext = io4(text) | |
| else: | |
| outtext = io1(text) | |
| """ | |
| #outtext = io2(text) | |
| outtext = generator(text, max_length=30, num_return_sequences=5) | |
| return outtext | |
| gr.Interface( | |
| inference, | |
| [gr.inputs.Textbox(label="Input", placeholder="trustworthy artificial intelligence")], | |
| #,gr.inputs.Dropdown(choices=["distilgpt2","gpt2-medium","gpt2-large","gpt2-xl"], type="value", default="gpt2-medium", label="model")], | |
| gr.outputs.Textbox(label="gpt-2 proposal"), | |
| #title=title, | |
| #description=description, | |
| cache_examples=True).launch(enable_queue=True) | |
| #TODO: add credits at bottom |