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| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| import torch | |
| import gradio as gr | |
| tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-125m") | |
| model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-neo-125m") | |
| def text_generation(input_text, seed): | |
| input_ids = tokenizer(input_text, return_tensors="pt").input_ids | |
| torch.manual_seed(seed) # Max value: 18446744073709551615 | |
| outputs = model.generate(input_ids, do_sample=True, min_length=50, max_length=200) | |
| generated_text = tokenizer.batch_decode(outputs, skip_special_tokens=True) | |
| return generated_text | |
| title = "Text Generator Demo GPT-Neo" | |
| description = "Text Generator Application" | |
| # gr.Interface( | |
| # text_generation, | |
| # [gr.inputs.Textbox(lines=2, label="Enter input text"), gr.inputs.Number(default=10, label="Enter seed number")], | |
| # [gr.outputs.Textbox(type="text", label="Text Generated")], | |
| # title=title, | |
| # description=description, | |
| # theme="huggingface" | |
| # ).launch() | |
| examples = [ | |
| ["Once upon a time", 123], | |
| ["In a galaxy far, far away", 42], | |
| # ["Lorem ipsum dolor sit amet", 999], | |
| ["The owners were also directed", 23], | |
| ] | |
| iface = gr.Interface( | |
| fn=text_generation, | |
| inputs=[ | |
| gr.inputs.Textbox(lines=2, label="Enter input text"), | |
| gr.inputs.Number(default=10, label="Enter seed number") | |
| ], | |
| outputs=gr.outputs.Textbox(type="text", label="Text Generated"), | |
| title=title, | |
| description=description, | |
| theme="huggingface", | |
| examples=examples | |
| ) | |
| iface.launch() |