Instructions to use knowledge-computing/geolm-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use knowledge-computing/geolm-base-cased with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("knowledge-computing/geolm-base-cased") model = AutoModel.from_pretrained("knowledge-computing/geolm-base-cased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b9ae055c82157c32e0a2d676dd46463c5345e3e5af81f4d1b3c24d02cbecda8
- Size of remote file:
- 431 MB
- SHA256:
- 988db701fa82256e601aa8464eb53ebbedb145018db2418b736ff43803b23245
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.