Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use lemon-mint/LLM-Router-Test-02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lemon-mint/LLM-Router-Test-02 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lemon-mint/LLM-Router-Test-02")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lemon-mint/LLM-Router-Test-02") model = AutoModelForSequenceClassification.from_pretrained("lemon-mint/LLM-Router-Test-02") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46d8d66de3e69f9b3ad43b6981a9f126930d936546c0b39e20a14143656ee060
- Size of remote file:
- 5.3 kB
- SHA256:
- 6cd70964e5e155e3d9e02009e7381f4c61e0c8c33da0d5e883018b628eea3fd4
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