merge
This is a testing model using the zeroing method used by elinas/Llama-3-15B-Instruct-zeroed.
If this model pans out in the way I hope, Ill heal it then reupload with a custom model card like the others. currently this is just an experiment.
In case anyone asks AbL3In-15b literally means:
Ab = Abliterated
L3 = Llama-3
In = Instruct
15b = its 15b perameters
GGUF's
Merge Details
Merge Method
This model was merged using the passthrough merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
dtype: bfloat16
merge_method: passthrough
slices:
- sources:
- layer_range: [0, 24]
model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3
- sources:
- layer_range: [8, 24]
model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3
parameters:
scale:
- filter: o_proj
value: 0.0
- filter: down_proj
value: 0.0
- value: 1.0
- sources:
- layer_range: [8, 24]
model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3
parameters:
scale:
- filter: o_proj
value: 0.0
- filter: down_proj
value: 0.0
- value: 1.0
- sources:
- layer_range: [24, 32]
model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 67.46 |
AI2 Reasoning Challenge (25-Shot) | 61.77 |
HellaSwag (10-Shot) | 78.42 |
MMLU (5-Shot) | 66.57 |
TruthfulQA (0-shot) | 52.53 |
Winogrande (5-shot) | 74.74 |
GSM8k (5-shot) | 70.74 |
- Downloads last month
- 51
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 SteelStorage/AbL3In-15B
Spaces using SteelStorage/AbL3In-15B 6
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard61.770
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard78.420
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard66.570
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard52.530
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard74.740
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard70.740