BAAI / feature-extraction Open weights updated 2 years ago

bge-large-en-v1.5

If you are looking for a model that supports more languages, longer texts, and other retrieval methods, you can try using bge-m3.

Params

340 M

Context

512

Downloads 30d

8.2 M

Likes

781

Commercial use: allowed mit Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 106 days

▲ 1.9 M in the last 30 days (18.6%)

13.8 M8.2 M

Jul 28Sep 1Oct 6Nov 10

Can you run it?

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	1.3 GB	2.0 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: BertModel
Parameters: 340 M
Tensor type: F32
Context length: 512
Vocabulary: 30,522
Layers / heads: 24 / 16
Licence: mit
First seen on the Hub: 2023-09-12
Training datasets: undisclosed
MTEB ArguAna (reported): 77.027
MTEB BIOSSES (reported): 84.206737984757
MTEB ArxivClusteringP2P (reported): 48.56707792675
MTEB ArxivClusteringS2S (reported): 43.194533891824
MTEB BiorxivClusteringP2P (reported): 39.71453833765
MTEB BiorxivClusteringS2S (reported): 36.901083492844
MTEB AskUbuntuDupQuestions (reported): 77.823616057688
MTEB Banking77Classification (reported): 87.771893109649
MTEB CQADupstackAndroidRetrieval (reported): 32.795
MTEB AmazonPolarityClassification (reported): 92.394770195742
MTEB AmazonReviewsClassification (en) (reported): 47.807127928703
MTEB AmazonCounterfactualClassification (en) (reported): 69.693866480435
Added to our catalog: 2026-07-28

Compare with any feature-extraction model

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Appears in

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