Instructions to use GalacticLinguists/rm-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GalacticLinguists/rm-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GalacticLinguists/rm-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GalacticLinguists/rm-model") model = AutoModelForSequenceClassification.from_pretrained("GalacticLinguists/rm-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 756dd1fdc9d08510f3c874a37367d93c13548bcbd0b0ac0b0c0b76f91aca20b8
- Size of remote file:
- 1.11 GB
- SHA256:
- 304aa89a771a5dce1b53d5057eb7334a85bc3ef922057c489486c82127305e31
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