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@@ -20,7 +20,7 @@ The model was trained using a state-of-the-art distillation pipeline and an inst
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  Llama-3.1-SuperNova-Lite excels in both benchmark performance and real-world applications, providing the power of large-scale models in a more compact, efficient form ideal for organizations seeking high performance with reduced resource requirements.
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  # Evaluations
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- We will be submitting this model to the OpenLLM Leaderboard for a more conclusive benchmark - but here are our internal benchmarks using the main branch of lm evaluation harness:
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  | Benchmark | SuperNova-Lite | Llama-3.1-8b-Instruct |
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  |-------------|----------------|----------------------|
@@ -30,7 +30,4 @@ We will be submitting this model to the OpenLLM Leaderboard for a more conclusiv
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  | BBH | 51.1 | 50.6 |
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  | GPQA | 31.2 | 29.02 |
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- The script used for evaluation can be found inside this repository under /eval.sh, or click [here](https://huggingface.co/arcee-ai/Llama-3.1-SuperNova-Lite/blob/main/eval.sh)
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- # note
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- This readme will be edited regularly on September 10, 2024 (the day of release). After the final readme is in place we will remove this note.
 
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  Llama-3.1-SuperNova-Lite excels in both benchmark performance and real-world applications, providing the power of large-scale models in a more compact, efficient form ideal for organizations seeking high performance with reduced resource requirements.
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  # Evaluations
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+ Here are our internal benchmarks using the main branch of lm evaluation harness:
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  | Benchmark | SuperNova-Lite | Llama-3.1-8b-Instruct |
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  |-------------|----------------|----------------------|
 
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  | BBH | 51.1 | 50.6 |
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  | GPQA | 31.2 | 29.02 |
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+ The script used for evaluation can be found inside this repository under /eval.sh, or click [here](https://huggingface.co/arcee-ai/Llama-3.1-SuperNova-Lite/blob/main/eval.