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Runtime error
| import gradio as gr | |
| from transformers import pipeline | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| tokenizer = AutoTokenizer.from_pretrained("facebook/galactica-1.3b") | |
| model = AutoModelForCausalLM.from_pretrained("facebook/galactica-1.3b") | |
| text2text_generator = pipeline("text-generation", model=model, tokenizer=tokenizer, num_workers=2) | |
| def predict(text, max_length=64, temperature=0.7, do_sample=True): | |
| text = text.strip() | |
| out_text = text2text_generator(text, max_length=max_length, | |
| temperature=temperature, | |
| do_sample=do_sample, | |
| eos_token_id = tokenizer.eos_token_id, | |
| bos_token_id = tokenizer.bos_token_id, | |
| pad_token_id = tokenizer.pad_token_id, | |
| )[0]['generated_text'] | |
| out_text = "<p>" + out_text + "</p>" | |
| out_text = out_text.replace(text, text + "<b><span style='background-color: #ffffcc;'>") | |
| out_text = out_text + "</span></b>" | |
| out_text = out_text.replace("\n", "<br>") | |
| return out_text | |
| iface = gr.Interface( | |
| fn=predict, | |
| inputs=[ | |
| gr.inputs.Textbox(lines=5, label="Input Text"), | |
| gr.inputs.Slider(minimum=32, maximum=256, default=64, label="Max Length"), | |
| gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.7, step=0.1, label="Temperature"), | |
| gr.inputs.Checkbox(label="Do Sample"), | |
| ], | |
| outputs=gr.HTML(), | |
| description="Galactica Base Model", | |
| examples=[[ | |
| "The attention mechanism in LLM is", | |
| 128, | |
| 0.7, | |
| True | |
| ], | |
| [ | |
| "Title: Attention is all you need\n\nAbstract:", | |
| 128, | |
| 0.7, | |
| True | |
| ] | |
| ] | |
| ) | |
| iface.launch() |