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('sentence-similarity', 'Snowflake/snowflake-arctic-embed-l-v2.0'); - Inference
- Notebooks
- Google Colab
- Kaggle
Set CTX Length to 2048
#19
by michaelfeil - opened
No description provided.
This model has an 8k context length. This change appears incorrect.
michaelfeil changed pull request status to closed
right, we need to also truncate the context length of the abs pos embeddings vector for bert.