Notes
This is an experiment to try these extra SLERP parameters @bamec66557 uses in bamec66557/Qwen-2.5-14B-MINUS, but with the models I'm working on now. Do they make a difference to mergekit-gui? We'll see.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: sometimesanotion/Qwen2.5-14B-Vimarckoso-v3
- model: sometimesanotion/Lamarck-14B-v0.6
merge_method: slerp
base_model: sometimesanotion/Qwen2.5-14B-Vimarckoso-v3
dtype: float32
out_dtype: bfloat16
parameters:
t: [0.3, 0.6, 0.8, 0.6, 0.3]
regularization:
- method: gradient_penalty
scale: 0.07
- method: weight_clipping
clip_range: [-0.2, 0.2]
- method: random_noise
scale: 0.005
- method: attention_dropout
scale: 0.03
postprocessing:
- operation: entropy_regularization
scale: 0.07
- operation: non_linear_scaling
parameters:
function: gelu
- operation: sharpening
intensity: 0.7
- operation: gaussian_smoothing
sigma: 0.2
- operation: normalize
- operation: dynamic_scaling
scale_range: [0.97, 1.03]
- operation: smoothing
parameters:
adaptive: true
range: [0.97, 1.03]
kernel_size: 5
- Downloads last month
- 2
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for sometimesanotion/Qwen2.5-14B-MinusLike-Slerp-Experimental
Merge model
this model