BAAI / feature-extraction updated 2 years ago

bge-small-zh-v1.5

Name: bge-small-zh-v1.5
Author: BAAI

FlagEmbedding can map any text to a low-dimensional dense vector which can be used for tasks like retrieval, classification, clustering, or semantic search. And it also can be used in vector databases for LLMs.

Params

20 M

Context

512

Downloads 30d

4.8 M

Likes

133

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

Download history

daily snapshots · 10 days

4.8 M4.6 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.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	f32	0.1 GB	0.6 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: 20 M
Tensor type: F32
Context length: 512
Vocabulary: 21,128
Layers / heads: 4 / 8
Licence: mit
First seen on the Hub: 2023-09-12
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Compare with

bge-small-en-v1.5 72.4 M bge-base-en-v1.5 10.0 M all-MiniLM-L6-v2 2.9 M bge-base-en-v1.5 2.2 M bge-large-zh-v1.5 1.8 M bge-base-zh-v1.5 1.7 M

Appears in

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