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