BAAI
BGE M3
Aktuell
31.0MDownloads3.1KLikesJan 2024Veröffentlicht8K TokenKontextMITLizenz84 StarkQualität
BGE M3 (0.5680000185966492B parameters) requires approximately 4.1 GB of VRAM with F16 quantization. For the best balance of quality and speed, we recommend hardware with at least 5 GB of VRAM.
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— kopieren & einfügen, um lokal auszuführenCopy-paste commands to run BGE M3 on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "BAAI/bge-m3" \
--hf-file "bge-m3-F16.gguf" \
-c 4096 -ngl 99Quick specs
Parameters0.57B
Architecturedense
Context8K tokens
Modalityembedding
Min RAM0.2 GB
Rec. RAM1.2 GB (F16)
LicenseMIT
FamilyBGE
✓ RAG
About this model
- •Multi-Functionality: It can simultaneously perform the three common retrieval functionalities of embedding model: dense retrieval, multi-vector...
- •Multi-Linguality: It can support more than 100 working languages
- •Multi-Granularity: It is able to process inputs of different granularities, spanning from short sentences to long documents of up to 8192 tokens
Verwandte Modelle
Schnellauswahl
Beste Hardware
Top-Empfehlungen für BGE M3
Dieses Modell ausführen
Quantisierungsoptionen
VRAM-Schätzungen nach Quantisierungsstufe
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.2 GB | Low | — |
Q3_K_S | 3 | 0.3 GB | Low | — |
NVFP4 | 4 | 0.3 GB | Medium | — |
Q4_K_M | 4 | 0.3 GB | Medium | — |
Q5_K_M | 5 | 0.4 GB | High | — |
Q6_K | 6 | 0.5 GB | High | — |
Q8_0 | 8 | 0.6 GB | Very High | — |
F16 | 16 | 1.2 GB | Maximum | — |
Hardware-Kompatibilität
Eignungsschätzungen für alle Hardware
Computing compatibility...
Speicheraufschlüsselung
Reference: RTX 2060 6GB
Weights1.2 GB
KV Cache1.1 GB
Runtime1.2 GB
Headroom0.6 GB
Häufig gestellte Fragen
FAQ — BGE M3
Siehe auch