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--- |
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language: en |
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tags: |
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- en |
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- english |
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- gpt2 |
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- gpt3 |
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- text-generation |
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- lm |
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- nlp |
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datasets: |
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- cnn_dailymail |
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widget: |
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- text: "Ever noticed how plane seats appear to be getting smaller and smaller? " |
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inference: |
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parameters: |
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max_length: 100 |
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do_sample: True |
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temperature: 0.15 |
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--- |
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# GPT-3 small |
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Pretrained GPT-3 small, it's architecture intentionally resembles that of GPT-3, model was trained on CNN Daily Mail News dataset for text generation |
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# How to use the model |
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~~~~ |
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from transformers import GPT2Tokenizer, GPTNeoForCausalLM |
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tokenizer = GPT2Tokenizer.from_pretrained('gpt3-small-finetune-cnndaily-news') |
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model = GPTNeoForCausalLM.from_pretrained('gpt3-small-finetune-cnndaily-news') |
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text = "Ever noticed how plane seats appear to be getting smaller and smaller? " |
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input_ids = tokenizer.encode(text, return_tensors='pt') |
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max_length = 150 |
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sample_outputs = model.generate(input_ids, do_sample=True, max_length=max_length,temperature = 0.15) |
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for i, sample_output in enumerate(sample_outputs): |
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print(">> Generated text {}\n\n{}".format(i+1, tokenizer.decode(sample_output.tolist()))) |
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print('\n---') |
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~~~~ |
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## Author |
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` |
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Phan Minh Toan |
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` |