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import gradio as gr
import transformers
import tokenizers
# https://huggingface.co/docs/hub/spaces-sdks-gradio
tokenizer_bert = BertTokenizerFast.from_pretrained('bert-base-chinese',
additional_special_tokens=["<s>","<pad>","</s>","<unk>","<mask>"],
pad_token='<pad>' ,max_len=512)
configuration = GPT2Config(vocab_size=25000, n_layer=8)
model = GPT2LMHeadModel(config=configuration)
#%%
path2pytorch_model = "pytorch_model.bin"
model.load_state_dict(torch.load(path2pytorch_model))
generator = pipeline('text-generation', model=model, tokenizer=tokenizer_bert)
def generate(prompt):
outputs = generator(prompt, max_length=30, num_return_sequences=5, num_beams=10, top_p=0.999, repetition_penalty=1.5)
return outputs[0]['generated_text']
iface = gr.Interface(fn=generate, inputs="text", outputs="text")
iface.launch()
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