Text Classification
Transformers
TensorBoard
Safetensors
English
modernbert
cross-encoder
sequence-classification
text-embeddings-inference
Instructions to use xpmir/cross-encoder-ettin-68m-ADR-MSE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xpmir/cross-encoder-ettin-68m-ADR-MSE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xpmir/cross-encoder-ettin-68m-ADR-MSE")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xpmir/cross-encoder-ettin-68m-ADR-MSE") model = AutoModelForSequenceClassification.from_pretrained("xpmir/cross-encoder-ettin-68m-ADR-MSE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fa7b902a3e563bcfff3b9831e6ed2ff6590b1b6114a7af61b236f66b0f9f2e5
- Size of remote file:
- 274 MB
- SHA256:
- c9ba843e4abd56b0e79914dae2a05ae2148a3d9e0db789cff9bdde2cc9315d25
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