Instructions to use morgana-rodrigues/gemma-2b-quant-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use morgana-rodrigues/gemma-2b-quant-4bit with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b") model = PeftModel.from_pretrained(base_model, "morgana-rodrigues/gemma-2b-quant-4bit") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from morgana-rodrigues/gemma-2b-quant-4bit: direct link, hf CLI and curl.
- Browser
- Download file 4.41 kB
-
https://huggingface.co/morgana-rodrigues/gemma-2b-quant-4bit/resolve/main/training_args.bin
- Command line
-
hf download hf://morgana-rodrigues/gemma-2b-quant-4bit/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/morgana-rodrigues/gemma-2b-quant-4bit/resolve/main/training_args.bin
4.41 kB
- Xet hash:
- cb1ecb26c7605faf01935d34ab5e18bb6cb6f434a10cba6b107cec38b06ec918
- Size of remote file:
- 4.41 kB
- SHA256:
- 0b3a0f1283bc1130d269cdd41250ff29f005a83b0d28249aa0cd8bfa888ad5c5
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