Instructions to use TiffanyH/philosophy-ROCBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TiffanyH/philosophy-ROCBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TiffanyH/philosophy-ROCBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TiffanyH/philosophy-ROCBERT") model = AutoModelForSequenceClassification.from_pretrained("TiffanyH/philosophy-ROCBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90d686b91b413a537e8281e94493aa7c6a4dc42d364905638c9b0c1f8997ebb2
- Size of remote file:
- 469 MB
- SHA256:
- a9363e9950de0cd434b66743a100ef330960a1434e5c7437d0b94a0d3f8618df
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