Instructions to use rppadmakumar/gemma-2b-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rppadmakumar/gemma-2b-finetuned with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b") model = PeftModel.from_pretrained(base_model, "rppadmakumar/gemma-2b-finetuned") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rppadmakumar/gemma-2b-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 4.48 kB
-
https://huggingface.co/rppadmakumar/gemma-2b-finetuned/resolve/main/training_args.bin
- Command line
-
hf download hf://rppadmakumar/gemma-2b-finetuned/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rppadmakumar/gemma-2b-finetuned/resolve/main/training_args.bin
4.48 kB
- Xet hash:
- 0afc71d9bc8fa4fa4c046915731c1e2344d7a19977be11f54a986e0d28910f22
- Size of remote file:
- 4.48 kB
- SHA256:
- 0b7832f907614f68bf5c80fb29e3edd2e6721f13f01c3f1f49146bce513235dc
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