Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use sagarpatelcompstak/modernbert-crossencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sagarpatelcompstak/modernbert-crossencoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sagarpatelcompstak/modernbert-crossencoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sagarpatelcompstak/modernbert-crossencoder") model = AutoModelForSequenceClassification.from_pretrained("sagarpatelcompstak/modernbert-crossencoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sagarpatelcompstak/modernbert-crossencoder: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/sagarpatelcompstak/modernbert-crossencoder/resolve/main/training_args.bin
- Command line
-
hf download hf://sagarpatelcompstak/modernbert-crossencoder/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sagarpatelcompstak/modernbert-crossencoder/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- 3c9e7099a68fa12cf99c6895fa8bb56f2fe5b466089867337b96699251200050
- Size of remote file:
- 5.2 kB
- SHA256:
- cd9e6d27b03d193af3386e6148c780a3f7a35e6e3973c933881a9b1c595e72a7
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