Feature Extraction
Transformers
Safetensors
PyTorch
English
gemma3_text
sentence-similarity
search
retrieval
ranking
embeddings
semantic-search
bi-encoder
rag
text-embeddings-inference
Instructions to use GorankLabs/Rank-Embed-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GorankLabs/Rank-Embed-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="GorankLabs/Rank-Embed-1B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("GorankLabs/Rank-Embed-1B") model = AutoModel.from_pretrained("GorankLabs/Rank-Embed-1B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signature8f27212 -
Update README.md
Verified signature74b4b1b
-
Update README.md
Verified signature7ff1eb8 -
Update README.md
Verified signatured5c7275 -
Update README.md
Verified signature90d0ec0 -
Update README.md
Selen martinVerified signature8b9dc5d -
Upload folder using huggingface_hub
Verified signature00157e7 -
Upload folder using huggingface_hub
Verified signatureb9d7c5f -
Update README.md
Selen martinVerified signaturee3267f1 -
Create LICENSE
Selen martinVerified signature1822a56 -
Upload folder using huggingface_hub
Verified signatureefd62bc -
initial commit
Verified signature2a6cb8b