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7057142
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Upload app.py

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  1. app.py +52 -0
app.py ADDED
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+ from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration
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+ import torch
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+ import gradio as gr
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+
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+ mname = "facebook/blenderbot-400M-distill"
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+ model = BlenderbotForConditionalGeneration.from_pretrained(mname)
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+ tokenizer = BlenderbotTokenizer.from_pretrained(mname)
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+
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+ def take_last_tokens(inputs, note_history, history):
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+ """Filter the last 128 tokens"""
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+ if inputs['input_ids'].shape[1] > 128:
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+ inputs['input_ids'] = torch.tensor([inputs['input_ids'][0][-128:].tolist()])
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+ inputs['attention_mask'] = torch.tensor([inputs['attention_mask'][0][-128:].tolist()])
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+ note_history = ['</s> <s>'.join(note_history[0].split('</s> <s>')[2:])]
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+ history = history[1:]
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+ return inputs, note_history, history
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+
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+ def add_note_to_history(note, note_history):
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+ """Add a note to the historical information"""
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+ note_history.append(note)
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+ note_history = '</s> <s>'.join(note_history)
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+ return [note_history]
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+
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+ title = "Blenderbot Tokenizer with Conditional Generation State of the Art"
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+ description = """Blenderbot"""
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+
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+ def chat(message, history):
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+ history = history or []
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+ if history:
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+ history_useful = ['</s> <s>'.join([str(a[0])+'</s> <s>'+str(a[1]) for a in history])]
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+ else:
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+ history_useful = []
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+ history_useful = add_note_to_history(message, history_useful)
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+ inputs = tokenizer(history_useful, return_tensors="pt")
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+ inputs, history_useful, history = take_last_tokens(inputs, history_useful, history)
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+ reply_ids = model.generate(**inputs)
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+ response = tokenizer.batch_decode(reply_ids, skip_special_tokens=True)[0]
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+ history_useful = add_note_to_history(response, history_useful)
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+ list_history = history_useful[0].split('</s> <s>')
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+ history.append((list_history[-2], list_history[-1]))
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+ return history, history
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+
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+ gr.Interface(
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+ fn=chat,
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+ theme="huggingface",
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+ css=".footer {display:none !important}",
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+ inputs=["text", "state"],
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+ outputs=["chatbot", "state"],
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+ title=title,
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+ description=description,
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+ allow_flagging="never",
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+ ).launch()