Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use lemon-mint/LLM-Router-Test-01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lemon-mint/LLM-Router-Test-01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lemon-mint/LLM-Router-Test-01")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lemon-mint/LLM-Router-Test-01") model = AutoModelForSequenceClassification.from_pretrained("lemon-mint/LLM-Router-Test-01") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc4d92db42edc53a82642abb9d740334ca9f474b08865df93d365e32d6615ed7
- Size of remote file:
- 5.37 kB
- SHA256:
- 46756a51458c4f88337ce4592a6bb312a6e1c86f92f67f097d9cdd0b0b8b07a6
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