Text Classification
Transformers
TensorBoard
Safetensors
English
modernbert
cross-encoder
sequence-classification
text-embeddings-inference
Instructions to use xpmir/cross-encoder-ettin-68m-BCE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xpmir/cross-encoder-ettin-68m-BCE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xpmir/cross-encoder-ettin-68m-BCE")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xpmir/cross-encoder-ettin-68m-BCE") model = AutoModelForSequenceClassification.from_pretrained("xpmir/cross-encoder-ettin-68m-BCE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3eb8ad16511730960cf09b8880250b183f147894a4255fe5bc28b5a6dffd54ce
- Size of remote file:
- 274 MB
- SHA256:
- c435e49012c26c62ce76c7ab46a9cc642a6eb8b46e05888dd83858a7744d1b43
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