417 Downloads Updated 1 year ago
Updated 1 year ago
1 year ago
6a342d3f0558 · 9.1GB ·
This model is a medium-sized MoE implementation based on cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
A 2x7b configuration offers better performance than a standard 7b model even if loaded in 4 bit. (9G VRAM)
If this 2x7b model is loaded in 4 bit the hellaswag score is .8270 which is higher than the base model achieves on its own in full precision.
| Name | Quant method | Bits | Size (GB) | Max RAM required (GB) | Use case |
|---|---|---|---|---|---|
| exer/laser-dolphin-mixtral:2x7b-dpo-q5_K_M | Q5_K_M | 5 | 9.13 GB | 11.63 GB | large, very low quality loss - recommended |
| exer/laser-dolphin-mixtral:2x7b-dpo-q6_K | Q6_K | 6 | 10.57 | 13.07 | very large, extremely low quality loss |
This model follows the same prompt format as the aforementioned model.
Prompt format:
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant