Pasta-Lake-7b / README.md
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Adding Evaluation Results (#2)
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---
license: other
library_name: transformers
tags:
- mergekit
- merge
base_model:
- Test157t/Pasta-PrimaMaid-7b
- macadeliccc/WestLake-7B-v2-laser-truthy-dpo
model-index:
- name: Pasta-Lake-7b
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: 70.82
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Test157t/Pasta-Lake-7b
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: 87.91
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Test157t/Pasta-Lake-7b
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: 64.41
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Test157t/Pasta-Lake-7b
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: 68.28
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Test157t/Pasta-Lake-7b
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: 82.64
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Test157t/Pasta-Lake-7b
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: 64.37
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=Test157t/Pasta-Lake-7b
name: Open LLM Leaderboard
---
![image/png](https://cdn-uploads.huggingface.co/production/uploads/642265bc01c62c1e4102dc36/Q-4HMjTgR6cpLnuW6Ghk3.png)
Thanks to @Kooten the man the myth the legend we have exl2 quants: https://huggingface.co./models?search=Kooten/Pasta-Lake-7b-exl2
Thanks to @bartowski the homie for the additional exl2 quants, please show him some support aswell: https://huggingface.co./bartowski/Pasta-Lake-7b-exl2/tree/main
Thanks also to @konz00 for the gguf quants: https://huggingface.co./konz00/Pasta-Lake-7b-GGUF
Thanks to @Lewdiculus for the other GGUF quants: https://huggingface.co./Lewdiculous/Pasta-Lake-7b-GGUF
added ST preset files
### Models Merged
The following models were included in the merge:
* [Test157t/Pasta-PrimaMaid-7b](https://huggingface.co./Test157t/Pasta-PrimaMaid-7b)
* [macadeliccc/WestLake-7B-v2-laser-truthy-dpo](https://huggingface.co./macadeliccc/WestLake-7B-v2-laser-truthy-dpo)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
slices:
- sources:
- model: Test157t/Pasta-PrimaMaid-7b
layer_range: [0, 32]
- model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
layer_range: [0, 32]
merge_method: slerp
base_model: Test157t/Pasta-PrimaMaid-7b
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: float16
```
![image/png](https://cdn-uploads.huggingface.co/production/uploads/642265bc01c62c1e4102dc36/dfYLzaMs5KU4BtbQQKzat.png)
# [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_Test157t__Pasta-Lake-7b)
| Metric |Value|
|---------------------------------|----:|
|Avg. |73.07|
|AI2 Reasoning Challenge (25-Shot)|70.82|
|HellaSwag (10-Shot) |87.91|
|MMLU (5-Shot) |64.41|
|TruthfulQA (0-shot) |68.28|
|Winogrande (5-shot) |82.64|
|GSM8k (5-shot) |64.37|