Instructions to use Jainam/tinybert-reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jainam/tinybert-reranker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jainam/tinybert-reranker")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jainam/tinybert-reranker") model = AutoModelForSequenceClassification.from_pretrained("Jainam/tinybert-reranker") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d48cb20d6d18886257ae3fb865571a84f92d324b9e29a75f726dc5b0b96586fd
- Size of remote file:
- 17.5 MB
- SHA256:
- 0fac0be049dc228cfbcc5d6a34cbebba7843d6df9b1504bcd03114abb31a77bc
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