Instructions to use opticalmaterials/opticalpurebert_cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opticalmaterials/opticalpurebert_cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="opticalmaterials/opticalpurebert_cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("opticalmaterials/opticalpurebert_cased") model = AutoModelForMaskedLM.from_pretrained("opticalmaterials/opticalpurebert_cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c15bed47f8edae6f612d1bc66ecf523aef6453859881595414656f1291a14207
- Size of remote file:
- 433 MB
- SHA256:
- 482f41cc4a64abeb2bae9e42c366782b81a65119f38e73218d0abb72282039ae
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.