metadata
license: apache-2.0
tags:
- merge
- mergekit
- NousResearch/Meta-Llama-3-8B-Instruct
base_model:
- NousResearch/Meta-Llama-3-8B-Instruct
model-index:
- name: Aura-llama
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: 58.02
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TheSkullery/Aura-llama
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: 77.82
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TheSkullery/Aura-llama
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: 65.61
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TheSkullery/Aura-llama
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: 51.94
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TheSkullery/Aura-llama
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: 73.4
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TheSkullery/Aura-llama
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: 52.01
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TheSkullery/Aura-llama
name: Open LLM Leaderboard
Aura-llama
Now that the cute anime girl has your attention.
UPDATE: Model has been fixed
Aura-llama is using the methodology presented by SOLAR for scaling LLMs called depth up-scaling (DUS), which encompasses architectural modifications with continued pretraining. Using the solar paper as a base, I integrated Llama-3 weights into the upscaled layers, and In the future plan to continue training the model.
Aura-llama is a merge of the following models to create a base model to work from:
Merged Evals (Has Not Been Finetuned):
Aura-llama
- Avg: ?
- ARC: ?
- HellaSwag: ?
- MMLU: ?
- T-QA: ?
- Winogrande: ?
- GSM8K: ?
🧩 Configuration
dtype: float16
merge_method: passthrough
slices:
- sources:
- layer_range: [0, 12]
model: NousResearch/Meta-Llama-3-8B-Instruct
- sources:
- layer_range: [8, 20]
model: NousResearch/Meta-Llama-3-8B-Instruct
- sources:
- layer_range: [16, 28]
model: NousResearch/Meta-Llama-3-8B-Instruct
- sources:
- layer_range: [24, 32]
model: NousResearch/Meta-Llama-3-8B-Instruct
Metric | Value |
---|---|
Avg. | 63.13 |
AI2 Reasoning Challenge (25-Shot) | 58.02 |
HellaSwag (10-Shot) | 77.82 |
MMLU (5-Shot) | 65.61 |
TruthfulQA (0-shot) | 51.94 |
Winogrande (5-shot) | 73.40 |
GSM8k (5-shot) | 52.01 |