language:
- en tags:
- en
- english
- gpt2
- gpt3
- text-generation
- lm
- nlp datasets:
- cnn_dailymail widget:
- text: "Ever noticed how plane seats appear to be getting smaller and smaller? "
inference: parameters: max_length: 120 do_sample: True temperature: 0.8 ---\
GPT-3 small
Pretrained GPT-3 small, continuing the development of GPT NEO, with architecture that purposefully mimics that of GPT-3, model was trained on CNN Daily Mail News dataset for text generation.
How to use the model
from transformers import GPT2Tokenizer, GPTNeoForCausalLM
tokenizer = GPT2Tokenizer.from_pretrained('minhtoan/gpt3-small-finetune-cnndaily-news')
model = GPTNeoForCausalLM.from_pretrained('minhtoan/gpt3-small-finetune-cnndaily-news')
text = "Ever noticed how plane seats appear to be getting smaller and smaller? "
input_ids = tokenizer.encode(text, return_tensors='pt')
max_length = 150
sample_outputs = model.generate(input_ids, do_sample=True, max_length=max_length,temperature = 0.8)
for i, sample_output in enumerate(sample_outputs):
print(">> Generated text {}\n\n{}".format(i+1, tokenizer.decode(sample_output.tolist())))
print('\n---')
Author
Phan Minh Toan