mlx-community/snowflake-arctic-embed-l-v2.0-6bit
The Model mlx-community/snowflake-arctic-embed-l-v2.0-6bit was converted to MLX format from Snowflake/snowflake-arctic-embed-l-v2.0 using mlx-lm version 0.0.3.
Use with mlx
pip install mlx-embeddings
from mlx_embeddings import load, generate
import mlx.core as mx
model, tokenizer = load("mlx-community/snowflake-arctic-embed-l-v2.0-6bit")
# For text embeddings
output = generate(model, processor, texts=["I like grapes", "I like fruits"])
embeddings = output.text_embeds # Normalized embeddings
# Compute dot product between normalized embeddings
similarity_matrix = mx.matmul(embeddings, embeddings.T)
print("Similarity matrix between texts:")
print(similarity_matrix)
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Evaluation results
- accuracy on MTEB AmazonCounterfactualClassification (en-ext)test set self-reported67.039
- f1 on MTEB AmazonCounterfactualClassification (en-ext)test set self-reported55.181
- f1_weighted on MTEB AmazonCounterfactualClassification (en-ext)test set self-reported73.411
- ap on MTEB AmazonCounterfactualClassification (en-ext)test set self-reported17.991
- ap_weighted on MTEB AmazonCounterfactualClassification (en-ext)test set self-reported17.991
- main_score on MTEB AmazonCounterfactualClassification (en-ext)test set self-reported67.039
- accuracy on MTEB AmazonCounterfactualClassification (en)test set self-reported65.597
- f1 on MTEB AmazonCounterfactualClassification (en)test set self-reported60.244
- f1_weighted on MTEB AmazonCounterfactualClassification (en)test set self-reported68.998
- ap on MTEB AmazonCounterfactualClassification (en)test set self-reported29.762