intfloat / feature-extraction updated 5 months ago

multilingual-e5-large

Name: multilingual-e5-large
Author: intfloat

Multilingual E5 Text Embeddings: A Technical Report. Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, Furu Wei, arXiv 2024

Params

560 M

Context

512

Downloads 30d

7.2 M

Likes

1,252

Commercial use: allowed mit Not gated SAFETENSORS 94 languages View on Hugging Face ↗

Download history

daily snapshots · 55 days

▲ 374 K in the last 30 days (5.0%)

8.3 M6.7 M

Jul 28Aug 15Sep 2Sep 20

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	f32	2.2 GB	3.0 GB	✅ Runs comfortably

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Architecture: XLMRobertaModel
Parameters: 560 M
Tensor type: F32
Context length: 512
Vocabulary: 250,002
Layers / heads: 24 / 16
Licence: mit
First seen on the Hub: 2023-06-30
Training datasets: undisclosed
MTEB ArguAna (reported): 30.725
MTEB AmazonPolarityClassification (reported): 93.485548197173
MTEB AmazonReviewsClassification (de) (reported): 44.171956824006
MTEB AmazonReviewsClassification (en) (reported): 46.75122173518
MTEB AmazonReviewsClassification (es) (reported): 42.381556968556
MTEB AmazonReviewsClassification (fr) (reported): 40.844073216827
MTEB AmazonReviewsClassification (ja) (reported): 39.522976223819
MTEB AmazonReviewsClassification (zh) (reported): 38.039253339471
MTEB AmazonCounterfactualClassification (de) (reported): 69.282717877527
MTEB AmazonCounterfactualClassification (en) (reported): 73.327000921401
MTEB AmazonCounterfactualClassification (ja) (reported): 64.966194173687
MTEB AmazonCounterfactualClassification (en-ext) (reported): 67.624754490113
Added to our catalog: 2026-07-28

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