(GGUFs)
Slush is a two-stage model trained with high LoRA dropout, where stage 1 is a pretraining continuation on the base model, aimed at boosting the model's creativity and writing capabilities. This is then merged into the instruction tune model, and stage 2 is a fine tuning step on top of this to further enhance its roleplaying capabilities and/or to repair any damage caused in the stage 1 merge.
This is an initial experiment done on the at-this-point-infamous Llama 3.1 8B model, in an attempt to retain its smartness while addressing its abysmal lack of imagination/creativity. As always, feedback is welcome, and begone if you demand perfection.
The second stage, like the Sunfall series, follows the Silly Tavern preset, so ymmv in particular if you use some other tool and/or preset.
This update (v1.1) addresses some of the feedback from the first iteration by ramping down the training parameters, and also introduces a custom merge using mergekit.
Parameter suggestions:
I did all my testing with temp 1, min-p 0.1, DRY 0.8. I enabled XTC at higher contexts.
Training details:
- Stage 1 (continued pretraining)
- Target: meta-llama/Llama-3.1-8B (resulting LoRA merged into meta-llama/Llama-3.1-8B-Instruct)
- LoRA dropout 0.5 (motivation)
- LoRA rank 64, alpha 128 (motivation)
- LR cosine 4e-6
- LoRA+ with LR Ratio: 15
- Context size: 16384
- Gradient accumulation steps: 4
- Epochs: 1
- Stage 2 (fine tune)
- Target: Stage 1 model
- LoRA dropout 0.5
- LoRA rank 32, alpha 64
- LR cosine 5e-6 (min 5e-7)
- LoRA+ with LR Ratio: 15
- Context size: 16384
- Gradient accumulation steps: 4
- Epochs: 2
Merge Details
Merge Method
This model was merged using the TIES merge method using meta-llama/Llama-3.1-8B as a base.
Configuration
The following YAML configuration was used to produce this model:
models:
- model: stage1-on-instruct
parameters:
weight: 1.5
density: 1
- model: stage2-on-stage1
parameters:
weight: 1.5
density: 1
- model: meta-llama/Llama-3.1-8B-Instruct
parameters:
weight: 1
density: 1
merge_method: ties
base_model: meta-llama/Llama-3.1-8B
parameters:
weight: 1
density: 1
normalize: true
int8_mask: true
tokenizer_source: meta-llama/Llama-3.1-8B-Instruct
dtype: bfloat16