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Keras GPT2


Summary

Models

  • For GPT2_XLarge, needs to download 2 file parts gpt2_xlarge_webtext.1.h5 and gpt2_xlarge_webtext.2.h5.
Model Params FLOPs vocab_size LAMBADA PPL
GPT2_Base 163.04M 146.42G 50257 35.13
GPT2_Medium 406.29M 415.07G 50257 15.60
GPT2_Large 838.36M 890.28G 50257 10.87
GPT2_XLarge, +.2 1.638B 1758.3G 50257 8.63

Usage

from keras_cv_attention_models import gpt2

mm = gpt2.GPT2_Base()
_ = mm.run_prediction("hello world", num_samples=1, max_new_tokens=100)
# hello world. I mean, just because we call ourselves anorexic, with a very strong genetic, doesn't mean we are human.
#
# And so there we have it. And we've just got to get through going through the rest of our lives.
#
#
# I mean, it's a real challenge right now. And we know, we've already talked about the ethical issues. And so, I think, you know, the human body is a very dangerous thing, and the ethical issues
# ---------------

Set include_top=False to exclude model head layer.

from keras_cv_attention_models import gpt2

mm = gpt2.GPT2_Base(include_top=False)
# >>>> Load pretrained from: ~/.keras/models/gpt2_base_webtext.h5
print(f"{mm.output_shape = }")
# mm.output_shape = (None, 1024, 768)

Set pretrained="huggingface" for converting and loading weights from huggingface transformers pacakge.

from keras_cv_attention_models import gpt2

mm = gpt2.GPT2_Medium(pretrained="huggingface")
# Load and convert weights from huggingface
# >>>> Save to: ~/.keras/models/gpt2_medium_huggingface.h5
_ = mm.run_prediction("hello world", num_samples=1, max_new_tokens=100)
# hello world, and he'll meet you in the afternoon and ask you to think about your career, and then I'll return. I'll write something up, and after that I'll have you come over."<|endoftext|>BALTIMORE -- The Baltimore Sun has been the one to expose the violence and destruction of the Baltimore riots that led to the death of Freddie Gray, and it's not your typical public servant.
#
# The Sun, which is owned by the Baltimore-based News Corp, went public with
# ---------------