A Simple and Efficient PromptGen Inference Implementation In TensorFlow 2.
from gpt2 import GPT2
from gpt2_tokenizer import GPT2Tokenizer
from gpt2_causal_lm import GPT2CausalLMPreprocessor, GPT2CausalLM
sequence_length = 128
max_length = 1024
seed = 123
tokenizer = GPT2Tokenizer()
preprocessor = GPT2CausalLMPreprocessor(tokenizer=tokenizer, sequence_length=sequence_length)
gpt2_backbone = GPT2(vocabulary_size=50257, num_layers=6, num_heads=12, hidden_dim=768, intermediate_dim=3072,
max_sequence_length=1024)
# download form:
# https://huggingface.co/AUTOMATIC/promptgen-lexart/blob/main/pytorch_model.bin
pytorch_model = "pytorch_model.bin"
gpt2_backbone.load_weights_from_ckpt(pytorch_model)
gpt2_lm = GPT2CausalLM(
backbone=gpt2_backbone,
preprocessor=preprocessor, seed=seed)
z = gpt2_lm.generate(["a girl.", "a cat."], max_length=max_length)
print(z)Licenses for borrowed code can be found in following link:
- PromptGenerator - https://github.com/AUTOMATIC1111/stable-diffusion-webui-promptgen
- KerasNLP - https://github.com/keras-team/keras-nlp
- Transformers - https://github.com/huggingface/transformers
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