Bragi3
Too sloppy for my tastes.
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the NuSLERP merge method using meta-llama/Llama-3.1-70B as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: CrucibleLab/L3.3-70B-Loki-V2.0
parameters:
weight:
- filter: q_proj
value: [0.80, 0.30, 0.30, 0.30, 0.8]
- filter: k_proj
value: [0.70, 0.20, 0.20, 0.20, 0.7]
- filter: v_proj
value: [0.80, 0.40, 0.40, 0.40, 0.8]
- filter: o_proj
value: [0.90, 0.80, 0.80, 0.80, 0.9]
- filter: gate_proj
value: [0.80, 0.20, 0.20, 0.20, 0.8]
- filter: up_proj
value: [0.80, 0.30, 0.30, 0.30, 0.8]
- filter: down_proj
value: [0.90, 0.80, 0.80, 0.80, 0.9]
- filter: lm_head
value: 0.95
- value: 1
- model: schonsense/Tropoplectic
parameters:
weight:
- filter: q_proj
value: [0.20, 0.70, 0.70, 0.70, 0.2]
- filter: k_proj
value: [0.30, 0.80, 0.80, 0.80, 0.3]
- filter: v_proj
value: [0.20, 0.60, 0.60, 0.60, 0.2]
- filter: o_proj
value: [0.10, 0.25, 0.25, 0.25, 0.1]
- filter: gate_proj
value: [0.20, 0.80, 0.80, 0.80, 0.2]
- filter: up_proj
value: [0.20, 0.70, 0.70, 0.70, 0.2]
- filter: down_proj
value: [0.10, 0.25, 0.25, 0.25, 0.1]
- filter: lm_head
value: 0.05
- value: 0
base_model: meta-llama/Llama-3.1-70B
merge_method: nuslerp
parameters:
normalize: false
int8_mask: false
rescale: false
dtype: float32
out_dtype: bfloat16
chat_template: llama3
tokenizer:
source: union
pad_to_multiple_of: 8
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