Instructions to use owen198/philosophy-ROCBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use owen198/philosophy-ROCBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="owen198/philosophy-ROCBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("owen198/philosophy-ROCBERT") model = AutoModelForSequenceClassification.from_pretrained("owen198/philosophy-ROCBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2acef1a130cd7f21c9e1de15948f3e7e6f1a6461ad2bc20c7f3f940753c6f29c
- Size of remote file:
- 469 MB
- SHA256:
- 0a50eeed35bb54d5fa77e97f88ce4a12e73c35eb37a9041d153fe00667c3d4c9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.