Feature Extraction
Transformers
Safetensors
qwen3
sentence-similarity
text-embeddings-inference
reranking
Instructions to use Alibaba-NLP/E2Rank-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alibaba-NLP/E2Rank-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Alibaba-NLP/E2Rank-4B")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Alibaba-NLP/E2Rank-4B") model = AutoModel.from_pretrained("Alibaba-NLP/E2Rank-4B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d2b24ef4a62b3c2d70000cf66d8518884680fe89dd09c0fb0c4bda064d7998b
- Size of remote file:
- 11.4 MB
- SHA256:
- 40536e5564c6a3f8f384c2b4e8a72b54234bc70e7744771306ed26f2c4ca326b
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