Instructions to use Prahaladha/math-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prahaladha/math-checkpoints with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Prahaladha/math-checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download final/training_args.bin from Prahaladha/math-checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 6.1 kB
-
https://huggingface.co/Prahaladha/math-checkpoints/resolve/main/final/training_args.bin
- Command line
-
hf download hf://Prahaladha/math-checkpoints/final/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Prahaladha/math-checkpoints/resolve/main/final/training_args.bin
6.1 kB
- Xet hash:
- 17dd2a76d1a7a7ab5bc94ac307d6a7471169bb5b4807fd15b5b0c62a96d1dc9b
- Size of remote file:
- 6.1 kB
- SHA256:
- fea9b2323073e2318b97bc98274d44f984bd7e1c8a5db29693d8ef8e6ad45d8a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.