Sentence Similarity
sentence-transformers
ONNX
Safetensors
Transformers.js
bert
feature-extraction
mteb
arctic
snowflake-arctic-embed
Eval Results (legacy)
text-embeddings-inference
Instructions to use Snowflake/snowflake-arctic-embed-m 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 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Snowflake/snowflake-arctic-embed-m") 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 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'); - Inference
- Notebooks
- Google Colab
- Kaggle
add scarf
Browse files
README.md
CHANGED
|
@@ -3089,4 +3089,6 @@ We thank our modeling engineers, Danmei Xu, Luke Merrick, Gaurav Nuti, and Danie
|
|
| 3089 |
We thank our leadership, Himabindu Pucha, Kelvin So, Vivek Raghunathan, and Sridhar Ramaswamy, for supporting this work.
|
| 3090 |
We also thank the open-source community for producing the great models we could build on top of and making these releases possible.
|
| 3091 |
Finally, we thank the researchers who created BEIR and MTEB benchmarks.
|
| 3092 |
-
It is largely thanks to their tireless work to define what better looks like that we could improve model performance.
|
|
|
|
|
|
|
|
|
| 3089 |
We thank our leadership, Himabindu Pucha, Kelvin So, Vivek Raghunathan, and Sridhar Ramaswamy, for supporting this work.
|
| 3090 |
We also thank the open-source community for producing the great models we could build on top of and making these releases possible.
|
| 3091 |
Finally, we thank the researchers who created BEIR and MTEB benchmarks.
|
| 3092 |
+
It is largely thanks to their tireless work to define what better looks like that we could improve model performance.
|
| 3093 |
+
|
| 3094 |
+
<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=bda4e7d8-e0d8-4f43-8ecc-7bc1d1c4ed04" />
|