Instructions to use student-shriman/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use student-shriman/checkpoints with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("student-shriman/checkpoints") model = AutoModelForSeq2SeqLM.from_pretrained("student-shriman/checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from student-shriman/checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 3.71 kB
-
https://huggingface.co/student-shriman/checkpoints/resolve/main/training_args.bin
- Command line
-
hf download hf://student-shriman/checkpoints/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/student-shriman/checkpoints/resolve/main/training_args.bin
3.71 kB
- Xet hash:
- 269be8b168f3f5e73dbd85a8262f1898e69aa1ce5bf1f0a4cd451ec7e5350a9c
- Size of remote file:
- 3.71 kB
- SHA256:
- 55abd943a681e741988000cd642e2c796416770554fde8f447a36d7f4761bdbd
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