Spaces:
Sleeping
Sleeping
ubermenchh
commited on
Commit
•
8400d16
1
Parent(s):
7fff83f
Create app.py
Browse files
app.py
ADDED
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
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from threading import Thread
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import gradio as gr
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import torch
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MAX_INPUT_TOKEN_LENGTH = 4096
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model_id = 'HuggingFaceH4/zephyr-7b-beta'
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model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map='auto')
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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tokenizer.use_default_system_prompt = False
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def generate(input, chat_history=[], system_prompt=False, max_new_tokens=512, temperature=0.5, top_p=0.95, top_k=50, repetition_penalty=1.2):
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conversation = []
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if system_prompt:
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conversation.append({
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'role': 'system',
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'content': system_prompt
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})
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for user, assistant in chat_history:
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conversation.extend({
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'role': 'user',
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'content': user
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},
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{
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'role': 'assistant',
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'content': assistant
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})
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conversation.append({
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'role': 'user',
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'content': input
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})
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input_ids = tokenizer.apply_chat_template(conversation, return_tensors='pt')
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if input_ids.shape[1] > MAXX_INPUT_TOKEN_LENGTH:
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input_ids = input_ids[:, -MAX_INPUT_TOKEN_LENGTH:]
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gr.Warning(f"Trimed input from conversation as it was longer than {MAX_INPUT_TOKEN_LENGTH} tokens.")
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input_ids = input_ids.to(model.device)
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streamer = TextIteratorStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True)
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generate_kwargs = dict(
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{'input_ids': input_ids},
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streamer=streamer,
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max_new_tokens=max_new_tokens,
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do_sample=True,
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top_p=top_p,
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top_k=top_k,
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temperature=temperature,
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num_beams=1,
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repetition_penalty=repetition_penalty
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)
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t = Thread(target=model.generate, kwargs=generate_kwargs)
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t.start()
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outputs = []
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for text in streamer:
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outputs.append(text)
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yield ''.join(outputs)
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chat_interface = gr.ChatInterface(
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fn=generate,
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examples=[
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'What is GPT?',
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'What is Life?',
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'Who is Alan Turing'
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]
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)
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chat_interface.queue(max_size=20).launch()
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