library_name: transformers
tags:
- mergekit
- merge
base_model: []
model-index:
- name: L3-SMB-Instruct-12.2B-F32
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 43.03
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-SMB-Instruct-12.2B-F32
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 26.13
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-SMB-Instruct-12.2B-F32
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 4.08
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-SMB-Instruct-12.2B-F32
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 4.25
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-SMB-Instruct-12.2B-F32
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 9.62
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-SMB-Instruct-12.2B-F32
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 25.69
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-SMB-Instruct-12.2B-F32
name: Open LLM Leaderboard
L3-SMB-Instruct-12.2B-F32
This repo contains the full precision source code, in "safe tensors" format to generate GGUFs, GPTQ, EXL2, AWQ, HQQ and other formats. The source code can also be used directly.
For full information about this model, including:
- Details about this model and its use case(s).
- Context limits
- Special usage notes / settings.
- Any model(s) used to create this model.
- Template(s) used to access/use this model.
- Example generation(s)
- GGUF quants of this model
Please go to:
[ https://huggingface.co/DavidAU/L3-SthenoMaidBlackroot-12.2B-V1-INSTRUCT-ULTRA-F32-GGUF ]
Additional Quants:
[ https://huggingface.co/mradermacher/L3-SMB-Instruct-12.2B-F32-GGUF ]
Imatrix GGUF:
[ https://huggingface.co/mradermacher/L3-SMB-Instruct-12.2B-F32-i1-GGUF ]
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the passthrough merge method.
Models Merged
The following models were included in the merge:
- G:/7B/L3-SthenoMaidBlackroot-8B-V1
- G:/7B/Meta-Llama-3-8B-Instruct
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: G:/7B/Meta-Llama-3-8B-Instruct
layer_range: [0, 12]
- sources:
- model: G:/7B/L3-SthenoMaidBlackroot-8B-V1
layer_range: [6, 19]
parameters:
scale:
- filter: o_proj
value: 1
- filter: down_proj
value: 1
- value: 1
- sources:
- model: G:/7B/Meta-Llama-3-8B-Instruct
layer_range: [12, 18]
parameters:
scale:
- filter: o_proj
value: .5
- filter: down_proj
value: .5
- value: 1
- sources:
- model: G:/7B/Meta-Llama-3-8B-Instruct
layer_range: [18, 25]
parameters:
scale:
- filter: o_proj
value: .75
- filter: down_proj
value: .75
- value: 1
- sources:
- model: G:/7B/L3-SthenoMaidBlackroot-8B-V1
layer_range: [19, 32]
parameters:
scale:
- filter: o_proj
value: 1
- filter: down_proj
value: 1
- value: 1
merge_method: passthrough
dtype: float32
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 18.80 |
IFEval (0-Shot) | 43.03 |
BBH (3-Shot) | 26.13 |
MATH Lvl 5 (4-Shot) | 4.08 |
GPQA (0-shot) | 4.25 |
MuSR (0-shot) | 9.62 |
MMLU-PRO (5-shot) | 25.69 |