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from transformers import PretrainedConfig |
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class InfiMMHDConfig(PretrainedConfig): |
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model_type = "infimmhd" |
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def __init__( |
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self, |
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model_type="infimm-hd", |
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seq_length=1024, |
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tokenizer_type="LlamaTokenizer", |
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torch_dtype="bfloat16", |
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transformers_version="4.28.2", |
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use_cache=True, |
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use_flash_attn=False, |
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cross_attn_every_n_layers=4, |
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use_grad_checkpoint=False, |
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freeze_llm=True, |
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visual=None, |
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language=None, |
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image_token_id=None, |
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eoc_token_id=None, |
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**kwargs, |
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): |
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self.model_type = model_type |
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self.seq_length = seq_length |
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self.tokenizer_type = tokenizer_type |
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self.torch_dtype = torch_dtype |
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self.transformers_version = transformers_version |
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self.use_cache = use_cache |
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self.use_flash_attn = use_flash_attn |
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self.cross_attn_every_n_layers = cross_attn_every_n_layers |
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self.use_grad_checkpoint = use_grad_checkpoint |
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self.freeze_llm = freeze_llm |
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self.visual = visual |
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self.language = language |
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self.image_token_id = image_token_id |
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self.eoc_token_id = eoc_token_id |
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super().__init__(**kwargs) |
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