Text Classification
Transformers
PyTorch
Safetensors
English
xlm-roberta
zen
zenlm
hanzo
zen3
reranker
retrieval
text-embeddings-inference
Instructions to use zenlm/zen3-reranker-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zenlm/zen3-reranker-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zenlm/zen3-reranker-small")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zenlm/zen3-reranker-small") model = AutoModelForSequenceClassification.from_pretrained("zenlm/zen3-reranker-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 653f906c68241fc5864b1d745ba5c41e947a020ec4db336948616d3f7155c658
- Size of remote file:
- 17.1 MB
- SHA256:
- 9eb652ac4e40cc093272bbbe0f55d521cf67570060227109b5cdc20945a4489e
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