Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use philschmid/modernbert-llm-router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/modernbert-llm-router with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="philschmid/modernbert-llm-router")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("philschmid/modernbert-llm-router") model = AutoModelForSequenceClassification.from_pretrained("philschmid/modernbert-llm-router", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cfb6c323068bdfdfc31afd619f2a6546cc02c973cd8a09cad2f5dfad86fde708
- Size of remote file:
- 5.37 kB
- SHA256:
- 404a6257d442534242826a6028dc5e2bd88f6d9cbb60615b520d19bd9c1e9c1d
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