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Upload app.py
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app.py
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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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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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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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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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title = "Blenderbot Tokenizer with Conditional Generation State of the Art"
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description = """Blenderbot"""
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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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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()
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