Instructions to use dvdmrs09/gemma-py2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dvdmrs09/gemma-py2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-7b") model = PeftModel.from_pretrained(base_model, "dvdmrs09/gemma-py2") - Notebooks
- Google Colab
- Kaggle
Download checkpoint4.model.keras from dvdmrs09/gemma-py2: direct link, hf CLI and curl.
- Browser
- Download file 10.1 GB
-
https://huggingface.co/dvdmrs09/gemma-py2/resolve/main/checkpoint4.model.keras
- Command line
-
hf download hf://dvdmrs09/gemma-py2/checkpoint4.model.keras
-
curl -L -o checkpoint4.model.keras https://huggingface.co/dvdmrs09/gemma-py2/resolve/main/checkpoint4.model.keras
10.1 GB
- Xet hash:
- 1c7b98457d9492a8c1a1161029b3832a18a6e33d445edb5c375ca1a11d062869
- Size of remote file:
- 10.1 GB
- SHA256:
- 3d66f7c8224fe2c2242599a15c03a060708ffa86d8a63b66dfad9a07abcdb735
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