Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use SunitOutreach/modernbert-llm-router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SunitOutreach/modernbert-llm-router with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SunitOutreach/modernbert-llm-router")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SunitOutreach/modernbert-llm-router") model = AutoModelForSequenceClassification.from_pretrained("SunitOutreach/modernbert-llm-router") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3a972b8c741c3702d4d63c61c2ff6230a5ced4cb12e2d475f7419ac3669697d
- Size of remote file:
- 5.37 kB
- SHA256:
- b27dd9dda93ec199a18246c7bd0e8e5902ea7d283917c662205184b3ee9aae28
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.