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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import torch |
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import gradio as gr |
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tokenizer = AutoTokenizer.from_pretrained('TrLOX/gpt2-tdk') |
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model = AutoModelForCausalLM.from_pretrained('TrLOX/gpt2-tdk') |
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def text_generation(input_text, seed): |
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input_ids = tokenizer(input_text, return_tensors="pt").input_ids |
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torch.manual_seed(seed) |
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outputs = model.generate(input_ids, do_sample=True, min_length=50, max_length=200) |
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generated_text = tokenizer.batch_decode(outputs, skip_special_tokens=True) |
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return generated_text |
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title = "TDK GPT2" |
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description = "Title and description generation by keywords" |
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gr.Interface( |
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text_generation, |
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[gr.inputs.Textbox(lines=2, label="Enter input text"), gr.inputs.Number(default=10, label="Enter seed number")], |
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[gr.outputs.Textbox(type="auto", label="Text Generated")], |
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title=title, |
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description=description, |
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theme="huggingface" |
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).launch() |
