Instructions to use wterrrr/mamba_text_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wterrrr/mamba_text_classification with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wterrrr/mamba_text_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from wterrrr/mamba_text_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/wterrrr/mamba_text_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://wterrrr/mamba_text_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/wterrrr/mamba_text_classification/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 8e4c6c7c2b8a999c52b1c59891c7941bfaf3223b66a2397ba9bbff79be8a7921
- Size of remote file:
- 4.92 kB
- SHA256:
- 9360ef5643adf9824d0f9d4a37c7e131dcb4daa25154151cbc4963ea97e10d25
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.