Sentence Similarity
ANEForge
Safetensors
sentence-transformers
bert
apple-neural-engine
text-embeddings-inference
Instructions to use aneforge/e5-small-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ANEForge
How to use aneforge/e5-small-v2 with ANEForge:
# Run this model's encoder on the Apple Neural Engine, without CoreML. from aneforge.sentence_transformers import SentenceTransformer model = SentenceTransformer("aneforge/e5-small-v2") embeddings = model.encode(["Hello from the Neural Engine"], normalize_embeddings=True) - sentence-transformers
How to use aneforge/e5-small-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("aneforge/e5-small-v2") 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
File size: 200 Bytes
950c19a | 1 2 3 4 5 6 7 | {
"word_embedding_dimension": 384,
"pooling_mode_cls_token": false,
"pooling_mode_mean_tokens": true,
"pooling_mode_max_tokens": false,
"pooling_mode_mean_sqrt_len_tokens": false
} |