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from char_tokenizer import CharTokenizer
import gradio as gr
from transformers import GPT2LMHeadModel
tokenizer = CharTokenizer.load("saved_model/tokenizer.json")
model = GPT2LMHeadModel.from_pretrained("saved_model")
def generation(prompt, length):
tokens = tokenizer(prompt=str(length) + prompt)
output_ids = model.generate(tokens['input_ids'],
do_sample=True,
top_p=0.95,
max_length=100)
decoded_verse = tokenizer.decode(output_ids)[len(prompt) + 1:]
return decoded_verse
input_prompt = gr.inputs.Textbox()
input_length = gr.inputs.Dropdown([5, 6, 7])
gr.Interface(fn=generation, inputs=[input_prompt, input_length], outputs="text").launch() |