Text Classification
Transformers
TensorBoard
Safetensors
English
modernbert
reasoning
reasoning-datasets-competition
text-embeddings-inference
Instructions to use davanstrien/ModernBERT-based-Reasoning-Required with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/ModernBERT-based-Reasoning-Required with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davanstrien/ModernBERT-based-Reasoning-Required")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davanstrien/ModernBERT-based-Reasoning-Required") model = AutoModelForSequenceClassification.from_pretrained("davanstrien/ModernBERT-based-Reasoning-Required") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9856af7200e644773941c2add694ba2ef4615e567f6272b9f857133a45374f3
- Size of remote file:
- 5.37 kB
- SHA256:
- d56d3519b756a3e7c20860ab51a25283504888b2a4be02ee8aab066a497c7b2f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.