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32 lines
1.6 KiB
Python
32 lines
1.6 KiB
Python
from transformers.models.gemma.modeling_gemma import GemmaForSequenceClassification
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from transformers.models.llama.configuration_llama import LlamaConfig
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# Example where we only want to only modify the docstring
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class MyNewModel2Config(LlamaConfig):
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r"""
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This is the configuration class to store the configuration of a [`GemmaModel`]. It is used to instantiate an Gemma
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model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
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defaults will yield a similar configuration to that of the Gemma-7B.
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e.g. [google/gemma-7b](https://huggingface.co/google/gemma-7b)
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Configuration objects inherit from [`PreTrainedConfig`] and can be used to control the model outputs. Read the
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documentation from [`PreTrainedConfig`] for more information.
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Args:
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vocab_size (`int`, *optional*, defaults to 256000):
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Vocabulary size of the Gemma model. Defines the number of different tokens that can be represented by the
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`inputs_ids` passed when calling [`GemmaModel`]
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```python
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>>> from transformers import GemmaModel, GemmaConfig
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>>> # Initializing a Gemma gemma-7b style configuration
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>>> configuration = GemmaConfig()
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>>> # Initializing a model from the gemma-7b style configuration
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>>> model = GemmaModel(configuration)
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>>> # Accessing the model configuration
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>>> configuration = model.config
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```"""
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# Example where alllllll the dependencies are fetched to just copy the entire class
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class MyNewModel2ForSequenceClassification(GemmaForSequenceClassification):
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pass
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