Text Classification
Transformers
TensorBoard
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use underscore2/modernbert_large_slop_classifier_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use underscore2/modernbert_large_slop_classifier_v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="underscore2/modernbert_large_slop_classifier_v3", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("underscore2/modernbert_large_slop_classifier_v3") model = AutoModelForSequenceClassification.from_pretrained("underscore2/modernbert_large_slop_classifier_v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e45911efaeb022535ec76904e450e74de17b8612bcae76ab168ef93755667ec
- Size of remote file:
- 1.58 GB
- SHA256:
- 956e68ef4bba322fbdaf88675ddce29d2b9dcf8298b55dc8e15cc823d7ec77bf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.