Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
new
feature-extraction
mteb
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use NovaSearch/stella_en_400M_v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use NovaSearch/stella_en_400M_v5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NovaSearch/stella_en_400M_v5", 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 NovaSearch/stella_en_400M_v5 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("NovaSearch/stella_en_400M_v5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a76a072cba3157f6a210c17cb51862d2b893c245d5261643e16cbf4cf7d710de
- Size of remote file:
- 8.4 MB
- SHA256:
- a831055e5110e81c03ed6559f4ebf5842630f227ded6b6c18826700d548b990f
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