Instructions to use KasaiDanto/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use KasaiDanto/model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-2b-it") model = PeftModel.from_pretrained(base_model, "KasaiDanto/model") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from KasaiDanto/model: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/KasaiDanto/model/resolve/main/training_args.bin
- Command line
-
hf download hf://KasaiDanto/model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/KasaiDanto/model/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- acc9cbd0f2adb6d85bbc22054f76b71ca2631e4d3eb596231ba85d5d3f59c7c6
- Size of remote file:
- 5.24 kB
- SHA256:
- 804b22f39944de83bf0b1947728010fd472ca24601b8608c2ac45fa6284b98df
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.