👁 BAAI
BAAI
BGE Large EN v1.5
Current
14.8MDownloads689LikesSep 2023Released1K tokensContextMITLicense74 StrongQuality
BGE Large EN v1.5 (0.33500000834465027B parameters) requires approximately 4.0 GB of VRAM with F16 quantization. For the best balance of quality and speed, we recommend hardware with at least 5 GB of VRAM.
Get started
— copy & paste to run locallyCopy-paste commands to run BGE Large EN v1.5 on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "BAAI/bge-large-en-v1.5" \
--hf-file "bge-large-en-v1.5-F16.gguf" \
-c 4096 -ngl 99Quick specs
Parameters0.34B
Architecturedense
Context1K tokens
Modalityembedding
Min RAM0.1 GB
Rec. RAM0.7 GB (F16)
LicenseMIT
FamilyBGE
✓ RAG
About this model
- •1/9/2024: Release Activation-Beacon, an effective, efficient, compatible, and low-cost (training) method to extend the context length of LLM....
- •12/24/2023: Release LLaRA, a LLaMA-7B based dense retriever, leading to state-of-the-art performances on MS MARCO and BEIR. Model and code...
- •11/23/2023: Release LM-Cocktail, a method to maintain general capabilities during fine-tuning by merging multiple language models. Technical...
- •10/12/2023: Release LLM-Embedder, a unified embedding model to support diverse retrieval augmentation needs for LLMs. Technical Report
- •09/15/2023: The technical report and massive training data of BGE has been released
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Quantization options
VRAM estimates by quant level
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.1 GB | Low | — |
Q3_K_S | 3 | 0.2 GB | Low | — |
NVFP4 | 4 | 0.2 GB | Medium | — |
Q4_K_M | 4 | 0.2 GB | Medium | — |
Q5_K_M | 5 | 0.2 GB | High | — |
Q6_K | 6 | 0.3 GB | High | — |
Q8_0 | 8 | 0.4 GB | Very High | — |
F16 | 16 | 0.7 GB | Maximum | — |
Hardware compatibility
Fit estimates across all hardware
Computing compatibility...
Memory breakdown
Reference: RTX 2060 6GB
Weights0.7 GB
KV Cache1.5 GB
Runtime1.2 GB
Headroom0.6 GB
Frequently asked questions
FAQ — BGE Large EN v1.5
See also