Instructions to use ALBADDAWI/ft-google-gemma-2b-it-qlora-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ALBADDAWI/ft-google-gemma-2b-it-qlora-v2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b-it") model = PeftModel.from_pretrained(base_model, "ALBADDAWI/ft-google-gemma-2b-it-qlora-v2") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ALBADDAWI/ft-google-gemma-2b-it-qlora-v2: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/ALBADDAWI/ft-google-gemma-2b-it-qlora-v2/resolve/main/training_args.bin
- Command line
-
hf download hf://ALBADDAWI/ft-google-gemma-2b-it-qlora-v2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ALBADDAWI/ft-google-gemma-2b-it-qlora-v2/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- ebf430066fdd234b85699976c8987833f289d28cdd95492451baa6b50fcb0167
- Size of remote file:
- 4.92 kB
- SHA256:
- 83ad9040abacd283c39cf01e5885f8b693b6aa2d331573029557f17e10bfb9b5
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