Text Classification
Transformers
Safetensors
English
deberta-v2
citation-verification
retrieval-augmented-generation
rag
cross-lingual
deberta
cross-encoder
nli
attribution
Eval Results (legacy)
text-embeddings-inference
Instructions to use convexray/alignment-module-cross-encoder-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use convexray/alignment-module-cross-encoder-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="convexray/alignment-module-cross-encoder-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("convexray/alignment-module-cross-encoder-base") model = AutoModelForSequenceClassification.from_pretrained("convexray/alignment-module-cross-encoder-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from convexray/alignment-module-cross-encoder-base: direct link, hf CLI and curl.
- Browser
- Download file 8.66 MB
-
https://huggingface.co/convexray/alignment-module-cross-encoder-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://convexray/alignment-module-cross-encoder-base/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/convexray/alignment-module-cross-encoder-base/resolve/main/tokenizer.json
8.66 MB
File too large to display, you can check the raw version instead.