Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use specialsaucem/router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use specialsaucem/router with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="specialsaucem/router")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("specialsaucem/router") model = AutoModelForSequenceClassification.from_pretrained("specialsaucem/router", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f886a67f49a28a4a1cc064acb561d1699043e29d6531916eceb9f590529f8b8
- Size of remote file:
- 5.2 kB
- SHA256:
- 24cb833160f0a86d5b14624c6b4d525e87b16c462343a830481220dd52aa6eff
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