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minGPT / app.py

abidlabs HF staff

Update app.py

b6c0621 almost 2 years ago

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	import sys, os
	os.system("!git clone https://github.com/karpathy/minGPT/")
	sys.path.append('minGPT')

	from transformers import GPT2Tokenizer, GPT2LMHeadModel
	from mingpt.model import GPT
	from minGPT.mingpt.utils import set_seed

	use_mingpt = True # use minGPT or huggingface/transformers model?
	model_type = 'gpt2-xl'
	device = 'cuda'

	if use_mingpt:
	model = GPT.from_pretrained(model_type)
	else:
	model = GPT2LMHeadModel.from_pretrained(model_type)
	model.config.pad_token_id = model.config.eos_token_id # suppress a warning

	# ship model to device and set to eval mode
	model.to(device)
	model.eval();


	def generate(prompt='', num_samples=10, steps=20, do_sample=True):

	# tokenize the input prompt into integer input sequence
	tokenizer = GPT2Tokenizer.from_pretrained(model_type)
	if prompt == '': # to create unconditional samples we feed in the special start token
	prompt = '<\|endoftext\|>'
	encoded_input = tokenizer(prompt, return_tensors='pt').to(device)
	x = encoded_input['input_ids']
	x = x.expand(num_samples, -1)

	# forward the model `steps` times to get samples, in a batch
	y = model.generate(x, max_new_tokens=steps, do_sample=do_sample, top_k=40)

	for i in range(num_samples):
	out = tokenizer.decode(y[i].cpu().squeeze())
	print('-'*80)
	print(out)


	def infer(input):
	return generate(prompt=input, num_samples=3, steps=20)

	import gradio as gr

	gr.Interface(infer, "text", ["text", "text", "text"], examples=["I was commuting to my Silicon Valley job when I took a wrong turn. I"])