Text Classification
Transformers
TensorBoard
Safetensors
English
modernbert
cross-encoder
sequence-classification
text-embeddings-inference
Instructions to use xpmir/cross-encoder-ettin-68m-infoNCE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xpmir/cross-encoder-ettin-68m-infoNCE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xpmir/cross-encoder-ettin-68m-infoNCE")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xpmir/cross-encoder-ettin-68m-infoNCE") model = AutoModelForSequenceClassification.from_pretrained("xpmir/cross-encoder-ettin-68m-infoNCE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57192b7de902a8f532b8df38d3b6b62a05f78b6be9cb85d1a8a753bd83864799
- Size of remote file:
- 274 MB
- SHA256:
- 85c05607d8a917e73ba765469343f753305df3f26f290e6ec842be7a533bed9f
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