Sentence Similarity
sentence-transformers
ONNX
Safetensors
Transformers.js
xlm-roberta
feature-extraction
mteb
arctic
snowflake-arctic-embed
Eval Results (legacy)
Eval Results
text-embeddings-inference
Instructions to use Snowflake/snowflake-arctic-embed-l-v2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Snowflake/snowflake-arctic-embed-l-v2.0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Snowflake/snowflake-arctic-embed-l-v2.0") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers.js
How to use Snowflake/snowflake-arctic-embed-l-v2.0 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'Snowflake/snowflake-arctic-embed-l-v2.0'); - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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print(score, document)
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## Contact
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print(score, document)
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```
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This should produce the following scores
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```
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Query: what is snowflake?
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tensor(0.2715) The Data Cloud!
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tensor(0.0661) Mexico City of Course!
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Query: Where can I get the best tacos?
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tensor(0.2797) Mexico City of Course!
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tensor(0.1250) The Data Cloud!
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```
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## Contact
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