Sentence Similarity
sentence-transformers
ONNX
Safetensors
Transformers.js
gte
feature-extraction
mteb
arctic
snowflake-arctic-embed
custom_code
Eval Results (legacy)
Eval Results
Instructions to use Snowflake/snowflake-arctic-embed-m-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-m-v2.0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Snowflake/snowflake-arctic-embed-m-v2.0", trust_remote_code=True) 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-m-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-m-v2.0'); - Notebooks
- Google Colab
- Kaggle
fix TEI support
#9
by GarciaLnk - opened
- config.json +1 -1
config.json
CHANGED
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@@ -18,7 +18,7 @@
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"logn_attention_clip1": false,
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"logn_attention_scale": false,
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"max_position_embeddings": 8192,
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-
"model_type": "
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pack_qkv": true,
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"logn_attention_clip1": false,
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"logn_attention_scale": false,
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"max_position_embeddings": 8192,
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+
"model_type": "new",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pack_qkv": true,
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