Porting Gemma 2 transformers checkpoint #1678
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mattdangerw
reviewed
Jul 3, 2024
|
@mattdangerw @grasskin this PR is ready for review! Note: The KerasNLP Gemma 2 model works only on the JAX backend (for the time being) Also thanks to the Hugging Face team (Matt et. al.) for providing me with compute to work on this model. |
ariG23498
commented
Jul 4, 2024
Comment on lines
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| if transformers_config["model_type"] == "gemma": | ||
| port_weight( | ||
| keras_variable=decoder_layer.pre_ffw_norm.variables[0], | ||
| hf_weight_key=f"model.layers.{i}.post_attention_layernorm.weight", | ||
| ) | ||
| elif transformers_config["model_type"] == "gemma2": | ||
| port_weight( | ||
| keras_variable=decoder_layer.pre_ffw_norm.variables[0], | ||
| hf_weight_key=f"model.layers.{i}.pre_feedforward_layernorm.weight", | ||
| ) |
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This was done in order to align the gemma 1 and gemma 2 checkpoints.
I am open to better ways to go around it.
ariG23498
changed the title
|
Thanks! |
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Porting Gemma 2 transformers checkpoints in Keras NLP