Feature Extraction
Transformers
Safetensors
English
modernbert
Generated from Trainer
custom_code
text-embeddings-inference
Instructions to use GliteTech/DisamBertCrossEncoder-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GliteTech/DisamBertCrossEncoder-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="GliteTech/DisamBertCrossEncoder-base", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("GliteTech/DisamBertCrossEncoder-base", trust_remote_code=True) model = AutoModel.from_pretrained("GliteTech/DisamBertCrossEncoder-base", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 487ad0b3e59ae196073d0e3520b529344bd224dc9ec5245cdf3b7bb3812962a1
- Size of remote file:
- 596 MB
- SHA256:
- 2cb625d94dadd5a1929c852bb4728f74906eab0e8898e2300353ddaed125bb08
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