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---
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
---
<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Aura-llama-3 Data Card</title>
<link href="https://fonts.googleapis.com/css2?family=Quicksand:wght@400;500;600&display=swap" rel="stylesheet">
<style> body { font-family: 'Quicksand', sans-serif; background: linear-gradient(135deg, #2E3440 0%, #1A202C 100%); color: #D8DEE9; margin: 0; padding: 0; font-size: 16px; }
.container { width: 80%; max-width: 800px; margin: 20px auto; background-color: rgba(255, 255, 255, 0.02); padding: 20px; border-radius: 12px; box-shadow: 0 4px 10px rgba(0, 0, 0, 0.2); backdrop-filter: blur(10px); border: 1px solid rgba(255, 255, 255, 0.1); }
.header h1 { font-size: 28px; color: #ECEFF4; margin: 0 0 20px 0; text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.3); }
.update-section { margin-top: 30px; } .update-section h2 { font-size: 24px; color: #88C0D0; }
.update-section p { font-size: 16px; line-height: 1.6; color: #ECEFF4; }
.info img { width: 100%; border-radius: 10px; margin-bottom: 15px; }
a { color: #88C0D0; text-decoration: none; }
a:hover { color: #A3BE8C; }
pre { background-color: rgba(255, 255, 255, 0.05); padding: 10px; border-radius: 5px; overflow-x: auto; }
code { font-family: 'Courier New', monospace; color: #A3BE8C; } </style> </head> <body> <div class="container">
<div class="header">
<h1>Aura-llama-3</h1> </div> <div class="info">
<img src="https://cdn-uploads.huggingface.co/production/uploads/64545af5ec40bbbd01242ca6/QYpWMEXTe0_X3A7HyeBm0.webp" alt="Aura-llama image">
<p>Now that the cute anime girl has your attention.</p>
<p>UPDATE: Model has been fixed</p>
<p>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.</p>
<p>Aura-llama is a merge of the following models to create a base model to work from:</p>
<ul>
<li><a href="https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct">meta-llama/Meta-Llama-3-8B-Instruct</a></li>
<li><a href="https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct">meta-llama/Meta-Llama-3-8B-Instruct</a></li>
</ul>
</div>
<div class="update-section">
<h2>Merged Evals (Has Not Been Finetuned):</h2>
<p>Aura-llama</p>
<ul>
<li>Avg: 63.13</li>
<li>ARC: 58.02</li>
<li>HellaSwag: 77.82</li>
<li>MMLU: 65.61</li>
<li>T-QA: 51.94</li>
<li>Winogrande: 73.40</li>
<li>GSM8K: 52.01</li>
</ul>
</div>
<div class="update-section">
<h2>🧩 Configuration</h2>
<pre><code>
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
</code></pre>
</div>
</div>
</body>
</html>
# [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_TheSkullery__Aura-llama)
| 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|
|