Sentence Similarity
ANEForge
Safetensors
sentence-transformers
bert
apple-neural-engine
text-embeddings-inference
Instructions to use aneforge/gte-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ANEForge
How to use aneforge/gte-small with ANEForge:
# Run this model's encoder on the Apple Neural Engine, without CoreML. from aneforge.sentence_transformers import SentenceTransformer model = SentenceTransformer("aneforge/gte-small") embeddings = model.encode(["Hello from the Neural Engine"], normalize_embeddings=True) - sentence-transformers
How to use aneforge/gte-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("aneforge/gte-small") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download modules.json from aneforge/gte-small: direct link, hf CLI and curl.
- Browser
- Download file 385 Bytes
-
https://huggingface.co/aneforge/gte-small/resolve/main/modules.json
- Command line
-
hf download hf://aneforge/gte-small/modules.json
-
curl -L -o modules.json https://huggingface.co/aneforge/gte-small/resolve/main/modules.json
385 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Normalize", | |
| "type": "sentence_transformers.models.Normalize" | |
| } | |
| ] |