Sentence Similarity
sentence-transformers
ONNX
Safetensors
Transformers.js
nomic_bert
feature-extraction
mteb
arctic
snowflake-arctic-embed
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use Snowflake/snowflake-arctic-embed-m-long with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Snowflake/snowflake-arctic-embed-m-long with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Snowflake/snowflake-arctic-embed-m-long", 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.js
How to use Snowflake/snowflake-arctic-embed-m-long with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('sentence-similarity', 'Snowflake/snowflake-arctic-embed-m-long'); - Notebooks
- Google Colab
- Kaggle
add scarf
Browse files
README.md
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@@ -3086,4 +3086,6 @@ We thank our modeling engineers, Danmei Xu, Luke Merrick, Gaurav Nuti, and Danie
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We thank our leadership, Himabindu Pucha, Kelvin So, Vivek Raghunathan, and Sridhar Ramaswamy, for supporting this work.
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We also thank the open-source community for producing the great models we could build on top of and making these releases possible.
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Finally, we thank the researchers who created BEIR and MTEB benchmarks.
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It is largely thanks to their tireless work to define what better looks like that we could improve model performance.
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We thank our leadership, Himabindu Pucha, Kelvin So, Vivek Raghunathan, and Sridhar Ramaswamy, for supporting this work.
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We also thank the open-source community for producing the great models we could build on top of and making these releases possible.
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Finally, we thank the researchers who created BEIR and MTEB benchmarks.
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It is largely thanks to their tireless work to define what better looks like that we could improve model performance.
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<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=f528b5b4-2ba6-4fc6-8eed-259968d45577" />
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