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:
- 87f8ae0e8e0c84d883ab80228d2a49aa74ed19a14c3ade4af81f3116ef3af9fc
- Size of remote file:
- 13.8 MB
- SHA256:
- e5feb9bc0deb4b90bfee6d6deb1e9ba7318e44c3c659c01b6a5db7d222f93943
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