Samlagast-7B-bf16 / README.md
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---
language:
- en
license: apache-2.0
tags:
- mergekit
- merge
base_model:
- flemmingmiguel/MBX-7B-v3
- paulml/NeuralOmniWestBeaglake-7B
- FelixChao/Faraday-7B
- paulml/NeuralOmniBeagleMBX-v3-7B
model-index:
- name: Samlagast-7B-bf16
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 73.98
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kquant03/Samlagast-7B-bf16
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 89.34
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kquant03/Samlagast-7B-bf16
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 64.58
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kquant03/Samlagast-7B-bf16
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 73.9
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kquant03/Samlagast-7B-bf16
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 85.48
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kquant03/Samlagast-7B-bf16
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 67.55
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kquant03/Samlagast-7B-bf16
name: Open LLM Leaderboard
---
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6589d7e6586088fd2784a12c/eDLmpTkM4vuk8HiQcUzWv.png)
# To see what will happen.
[Join our Discord!](https://discord.gg/aEGuFph9)
[GGUF FILES HERE](https://huggingface.co/Kquant03/Samlagast-7B-GGUF)
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
### Merge Method
This model was merged using the [task arithmetic](https://arxiv.org/abs/2212.04089) merge method using [paulml/NeuralOmniBeagleMBX-v3-7B](https://huggingface.co/paulml/NeuralOmniBeagleMBX-v3-7B) as a base.
### Models Merged
The following models were included in the merge:
* [flemmingmiguel/MBX-7B-v3](https://huggingface.co/flemmingmiguel/MBX-7B-v3)
* [paulml/NeuralOmniWestBeaglake-7B](https://huggingface.co/paulml/NeuralOmniWestBeaglake-7B)
* [FelixChao/Faraday-7B](https://huggingface.co/FelixChao/Faraday-7B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
- model: paulml/NeuralOmniWestBeaglake-7B
parameters:
weight: 1
- model: FelixChao/Faraday-7B
parameters:
weight: 1
- model: flemmingmiguel/MBX-7B-v3
parameters:
weight: 1
- model: paulml/NeuralOmniBeagleMBX-v3-7B
parameters:
weight: 1
merge_method: task_arithmetic
base_model: paulml/NeuralOmniBeagleMBX-v3-7B
parameters:
normalize: true
int8_mask: true
dtype: float16
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Kquant03__Samlagast-7B-bf16)
| Metric |Value|
|---------------------------------|----:|
|Avg. |75.81|
|AI2 Reasoning Challenge (25-Shot)|73.98|
|HellaSwag (10-Shot) |89.34|
|MMLU (5-Shot) |64.58|
|TruthfulQA (0-shot) |73.90|
|Winogrande (5-shot) |85.48|
|GSM8k (5-shot) |67.55|