Text Classification
Transformers
Safetensors
modernbert
cross-encoder
context-compression
supercompress
neural-keep
text-embeddings-inference
Instructions to use arjunkshah21/sc-keep-crossencoder-v4-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arjunkshah21/sc-keep-crossencoder-v4-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="arjunkshah21/sc-keep-crossencoder-v4-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("arjunkshah21/sc-keep-crossencoder-v4-large") model = AutoModelForSequenceClassification.from_pretrained("arjunkshah21/sc-keep-crossencoder-v4-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from arjunkshah21/sc-keep-crossencoder-v4-large: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/arjunkshah21/sc-keep-crossencoder-v4-large/resolve/main/tokenizer.json
- Command line
-
hf download hf://arjunkshah21/sc-keep-crossencoder-v4-large/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/arjunkshah21/sc-keep-crossencoder-v4-large/resolve/main/tokenizer.json
3.58 MB
File too large to display, you can check the raw version instead.