Update modeling_internlm3.py (#18)
Browse files- Update modeling_internlm3.py (94cd46f35e87e1b3b2b82df73230bdb5275cd652)
- Update tokenization_internlm3.py (0f3d7019880c0b6f7a9d35b392d21cbfca07478b)
- modeling_internlm3.py +2 -1
- tokenization_internlm3.py +1 -1
    	
        modeling_internlm3.py
    CHANGED
    
    | @@ -793,7 +793,7 @@ class InternLM3Model(InternLM3PreTrainedModel): | |
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                Args:
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                    config: InternLM3Config
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                """
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            -
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                def __init__(self, config: InternLM3Config):
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                    super().__init__(config)
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                    self.padding_idx = config.pad_token_id
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| @@ -1070,6 +1070,7 @@ class KwargsForCausalLM(FlashAttentionKwargs, LossKwargs): ... | |
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            class InternLM3ForCausalLM(InternLM3PreTrainedModel, GenerationMixin):
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                _tied_weights_keys = ["lm_head.weight"]
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                _tp_plan = {"lm_head": "colwise_rep"}
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                Args:
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                    config: InternLM3Config
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                """
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            +
                _auto_class = "AutoModel"
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                def __init__(self, config: InternLM3Config):
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                    super().__init__(config)
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                    self.padding_idx = config.pad_token_id
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            class InternLM3ForCausalLM(InternLM3PreTrainedModel, GenerationMixin):
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            +
                _auto_class = "AutoModelForCausalLM"
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                _tied_weights_keys = ["lm_head.weight"]
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                _tp_plan = {"lm_head": "colwise_rep"}
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        tokenization_internlm3.py
    CHANGED
    
    | @@ -67,7 +67,7 @@ class InternLM3Tokenizer(PreTrainedTokenizer): | |
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                        Whether or not to add an initial space to the input. This allows to treat the leading word just as any
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                        other word. Again, this should be set with `from_slow=True` to make sure it's taken into account.
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                """
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            -
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                vocab_files_names = VOCAB_FILES_NAMES
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                model_input_names = ["input_ids", "attention_mask"]
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                        Whether or not to add an initial space to the input. This allows to treat the leading word just as any
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                        other word. Again, this should be set with `from_slow=True` to make sure it's taken into account.
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                """
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            +
                _auto_class = "AutoTokenizer"
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                vocab_files_names = VOCAB_FILES_NAMES
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                model_input_names = ["input_ids", "attention_mask"]
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