Instructions to use jla25/square_V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jla25/square_V1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jla25/square_V1") model = AutoModelForSeq2SeqLM.from_pretrained("jla25/square_V1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jla25/square_V1: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/jla25/square_V1/resolve/main/training_args.bin
- Command line
-
hf download hf://jla25/square_V1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jla25/square_V1/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 67bf341d686480702c469bd81a8d54611140151fc72705e01dd1f17dd01bd1a8
- Size of remote file:
- 5.3 kB
- SHA256:
- 5791b67868d15f2ac3b20c0727108bc3192cf91ebc49a7cedbbd23b2f51f1114
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