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---
library_name: transformers
tags:
- mergekit
- merge
base_model: []
model-index:
- name: L3-Stheno-v3.2-12.2B-Instruct
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: 40.28
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-Stheno-v3.2-12.2B-Instruct
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: 27.37
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-Stheno-v3.2-12.2B-Instruct
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: 4.98
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-Stheno-v3.2-12.2B-Instruct
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: 3.36
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-Stheno-v3.2-12.2B-Instruct
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: 10.31
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-Stheno-v3.2-12.2B-Instruct
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: 26.06
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=DavidAU/L3-Stheno-v3.2-12.2B-Instruct
name: Open LLM Leaderboard
---
<h2>L3-Stheno-v3.2-12.2B-Instruct - Float32</h2>
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.
<B>IMPORTANT: Highest Quality Settings / Optimal Operation Guide / Parameters and Samplers</B>
If you are going to use this model, (source, GGUF or a different quant), please review this document for critical parameter, sampler and advance sampler settings (for multiple AI/LLM aps).
This a "Class 2" (settings will enhance operation / optional adjustments) model:
For all settings used for this model (including specifics for its "class"), including example generation(s) and for advanced settings guide (which many times addresses any model issue(s)), including methods to improve model performance for all use case(s) as well as chat, roleplay and other use case(s) (especially for use case(s) beyond the model's design) please see:
[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]
REASON:
Regardless of "model class" this document will detail methods to enhance operations.
If the model is a Class 3/4 model the default settings (parameters, samplers, advanced samplers) must be set for "use case(s)" uses correctly. Some AI/LLM apps DO NOT have consistant default setting(s) which result in sub-par model operation. Like wise for Class 3/4 models (which operate somewhat to very differently than standard models) additional samplers and advanced samplers settings are required to "smooth out" operation, AND/OR also allow full operation for use cases the model was not designed for.
BONUS - Use these settings for ANY model, ANY repo, ANY quant (including source/full precision):
This document also details parameters, sampler and advanced samplers that can be use FOR ANY MODEL, FROM ANY REPO too - all quants, and of course source code operation too - to enhance the operation of any model.
[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]
NOTE:
I strongly suggest you also visit the DavidAU GGUF (below) repo too for more details in using this model ; especially if it is "Class 3" or "Class 4" to get maximum performance from the model.
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-Stheno-v3.2-12.2B-INSTRUCT-ULTRA-F32-GGUF ]
Additional Quants:
Imatrix GGUFs:
[ https://huggingface.co/mradermacher/L3-Stheno-v3.2-12.2B-Instruct-i1-GGUF ]
GGUFS:
[ https://huggingface.co/mradermacher/L3-Stheno-v3.2-12.2B-Instruct-GGUF ]
---
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/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/L3-8B-Stheno-v3.2
* G:/7B/Meta-Llama-3-8B-Instruct
### Configuration
The following YAML configuration was used to produce this model:
```yaml
slices:
- sources:
- model: G:/7B/Meta-Llama-3-8B-Instruct
layer_range: [0, 12]
- sources:
- model: G:/7B/L3-8B-Stheno-v3.2
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/L3-8B-Stheno-v3.2
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](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_DavidAU__L3-Stheno-v3.2-12.2B-Instruct)
| Metric |Value|
|-------------------|----:|
|Avg. |18.73|
|IFEval (0-Shot) |40.28|
|BBH (3-Shot) |27.37|
|MATH Lvl 5 (4-Shot)| 4.98|
|GPQA (0-shot) | 3.36|
|MuSR (0-shot) |10.31|
|MMLU-PRO (5-shot) |26.06|
|