Instructions to use MMADS/RoBERTa-OrgCulture-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MMADS/RoBERTa-OrgCulture-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MMADS/RoBERTa-OrgCulture-Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MMADS/RoBERTa-OrgCulture-Classifier") model = AutoModelForMaskedLM.from_pretrained("MMADS/RoBERTa-OrgCulture-Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5ebb248c6c06acac1ed075d97a9b85fab9980b929b88fa0aba33c8087c91394
- Size of remote file:
- 499 MB
- SHA256:
- ec59c1a94ea82e7545a4ef7ca360f01e1147b2df2b240b20e88eeee7e26a1213
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.