| import gradio as gr |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| from transformers import AutoModelForCausalLM, AutoModelWithLMHead, AutoTokenizer, pipeline |
| from transformers import GPT2Tokenizer, GPT2Model |
|
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|
|
| general_model = AutoModelForCausalLM.from_pretrained('youa/gpt2') |
| general_generator = pipeline("text-generation", model=general_model, tokenizer="youa/gpt2") |
| general_result = general_generator("Today is ", max_length=1500) |
| general_result[0]["generated_text"] |
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|
|
| def generator(start_your_text = ''): |
| result = general_generator(start_your_text) |
| return result[0]["generated_text"] |
|
|
| iface = gr.Interface(fn=generator, inputs="text", outputs="text") |
| iface.launch() |
