Sentence Similarity
sentence-transformers
Safetensors
Transformers
new
feature-extraction
mteb
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use Gem-Software/stella-v5.2-boost15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Gem-Software/stella-v5.2-boost15 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Gem-Software/stella-v5.2-boost15", trust_remote_code=True) 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] - Transformers
How to use Gem-Software/stella-v5.2-boost15 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Gem-Software/stella-v5.2-boost15", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 429 Bytes
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