intfloat / feature-extraction updated 4 months ago

multilingual-e5-large

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
7.5 M
Likes
1,238
Commercial use: allowed mit Not gated SAFETENSORS 94 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days
8.3 M7.5 M
Jul 28Jul 31Aug 3Aug 6

Can you run it?

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

FileQuantSizeEst. VRAMVerdict 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.

Specifications

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