Instructions to use faridlazuarda/valadapt-gemma-2-9b-it-arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use faridlazuarda/valadapt-gemma-2-9b-it-arabic with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-9b-it") model = PeftModel.from_pretrained(base_model, "faridlazuarda/valadapt-gemma-2-9b-it-arabic") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from faridlazuarda/valadapt-gemma-2-9b-it-arabic: direct link, hf CLI and curl.
- Browser
- Download file 143 MB
-
https://huggingface.co/faridlazuarda/valadapt-gemma-2-9b-it-arabic/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://faridlazuarda/valadapt-gemma-2-9b-it-arabic/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/faridlazuarda/valadapt-gemma-2-9b-it-arabic/resolve/main/adapter_model.safetensors
143 MB
- Xet hash:
- 2ecd4ece63cf50620421aaddb43d7afe52899e329984642c29bb221091c7bfa8
- Size of remote file:
- 143 MB
- SHA256:
- 2f41d83e93f05f82b1f18896d71019460704c9e5c5e181e619d19b0bc430c5c2
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