ArtusDev/MiniMaxAI_MiniMax-M2-EXL3
EXL3 quants of MiniMaxAI/MiniMax-M2 using exllamav3 for quantization.
⚠️ Requires ExLlamaV3 v0.0.12. ⚠️
Quants
| Quant | BPW | Head Bits | Size (GB) |
|---|---|---|---|
| 2.0_H6 | 2.0 | 6 | 59.2 |
| 2.39_H6 (optimized) | 2.39 | 6 | 59.2 |
| 2.5_H6 | 2.5 | 6 | 73.40 |
| 2.76_H7 (optimized) | 2.76 | 7 | 80.27 |
| 3.0_H6 | 3.0 | 6 | 87.63 |
| 3.22_H6 (optimized) | 3.22 | 6 | 93.48 |
| 3.5_H6 | 3.5 | 6 | 101.83 |
| 3.68_H7 (optimized) | 3.68 | 7 | 106.54 |
| 4.0_H6 | 4.0 | 6 | 116.06 |
| 4.25_H6 | 4.25 | 6 | 123.16 |
| 5.0_H6 | 5.0 | 6 | 144.1 |
| 6.0_H6 | 6.0 | 6 | 173.22 |
| 8.0_H8 | 8.0 | 8 | 229.92 |
How to Download and Use Quants
You can download quants by targeting specific size using the Hugging Face CLI.
Click for download commands
1. Install huggingface-cli:
pip install -U "huggingface_hub[cli]"
2. Download a specific quant:
huggingface-cli download ArtusDev/MiniMaxAI_MiniMax-M2-EXL3 --revision "5.0bpw_H6" --local-dir ./
EXL3 quants can be run with any inference client that supports EXL3, such as TabbyAPI. Refer to documentation for set up instructions.
Model tree for ArtusDev/MiniMaxAI_MiniMax-M2-EXL3
Base model
MiniMaxAI/MiniMax-M2