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* Add truncate_text option to tokenize This makes it possible to run tokenize on texts that are longer than the number of tokens that fit the context length without having to try to guess how to cut in number of characters beforehand * add doc, rename to just "truncate", use eot_token Co-authored-by: Jong Wook Kim <jongwook@openai.com>
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openai just released two new checkpoints. I haven't tested this branch; just merged in the changes. May be a good idea to look over it since you're more familiar with the codebase. Looks like they liked the idea of having a |
rom1504
reviewed
Jul 24, 2021
clip/clip.py
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| @@ -161,7 +182,7 @@ def patch_float(module): | |||
| return model, _transform(model.input_resolution.item()) | |||
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| def tokenize(texts: Union[str, List[str]], context_length: int = 77, truncate_text = False) -> torch.LongTensor: | |||
| def tokenize(texts: Union[str, List[str]], context_length: int = 77, truncate_text: bool = False) -> torch.LongTensor: | |||
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I think they named this truncate, let's do the same here ?
rom1504
approved these changes
Jul 24, 2021
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