Instructions to use snksharma/PEFT_expo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use snksharma/PEFT_expo with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("snksharma/PEFT_expo") model = AutoModelForSeq2SeqLM.from_pretrained("snksharma/PEFT_expo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from snksharma/PEFT_expo: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/snksharma/PEFT_expo/resolve/main/training_args.bin
- Command line
-
hf download hf://snksharma/PEFT_expo/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/snksharma/PEFT_expo/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- 6729478bc9104b6c87ec3cf52c44ebb65cb64beb8b2a3b47f4cc5b70ade124f8
- Size of remote file:
- 5.91 kB
- SHA256:
- 5551ddece3a72ac9becbe4a2da66cd61e8c89ce1a01f4ccd62e67f6046d636b4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.