Sentence Similarity
Transformers
PyTorch
Safetensors
English
bert
feature-extraction
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use Narsil/bge-base-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Narsil/bge-base-en with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Narsil/bge-base-en") model = AutoModel.from_pretrained("Narsil/bge-base-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fba985202b9b69365a26ded734d73272331ca99f4edc5d9f930417ed24fca294
- Size of remote file:
- 438 MB
- SHA256:
- 28fc2b9645965168920a1d7fdfeda96b9c1f189c84adb71a7ffe586c26d2e3e5
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