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from transformers import LlamaTokenizerFast |
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class LlamaTokenizerWrapper(LlamaTokenizerFast): |
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def __init__(self, **kwargs): |
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super().__init__(**kwargs) |
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self.im_start = "<|image_start|>" |
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self.im_end = "<|image_end|>" |
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self.ref_start = "<|ref_start>|" |
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self.ref_end = "<|ref_end|>" |
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self.box_start = "<|box_start|>" |
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self.box_end = "<|box_end|>" |
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self.quad_start = "<|quad_start>" |
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self.quad_end = "<|quad_end|>" |
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self.point_start = "<|point_start|>" |
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self.point_end = "<|point_end|>" |
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self.slice_start = "<|slice_start|>" |
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self.slice_end = "<|slice_end|>" |
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self.audio_start = "<|audio_start|>" |
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self.audio_end = "<|audio_end|>" |
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self.eos_token = "<|turn_end|>" |
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self.pad_token = "<|pad|>" |
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@property |
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def eos_id(self): |
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return self.eos_token_id |
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@property |
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def unk_id(self): |
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return self.unk_token_id |
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@property |
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def im_start_id(self): |
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return self.encode(self.im_start, add_special_tokens=False)[0] |
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@property |
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def im_end_id(self): |
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return self.encode(self.im_end, add_special_tokens=False)[0] |
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@property |
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def slice_start_id(self): |
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return self.encode(self.slice_start, add_special_tokens=False)[0] |
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@property |
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def slice_end_id(self): |
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return self.encode(self.slice_end, add_special_tokens=False)[0] |
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@property |
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def audio_start_id(self): |
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return self.encode(self.audio_start, add_special_tokens=False)[0] |
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@property |
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def audio_end_id(self): |
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return self.encode(self.audio_end, add_special_tokens=False)[0] |
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@property |
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def eos_token_id(self): |
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return self.encode(self.eos_token, add_special_tokens=False)[0] |
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@property |
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def pad_token_id(self): |
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return self.encode(self.eos_token, add_special_tokens=False)[0] |
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