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open-instruct-sni-13b

Text Generation

text-generation-inference

Inference Endpoints

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hamishivi commited on Jun 9, 2023

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@@ -44,7 +44,7 @@ Here is the performance of this model across benchmarks explored in our paper [H
 | MMLU 0-shot | MMLU 5-shot | GSM Direct | GSM CoT | BBH Direct | BBH CoT | TydiQA Gold-Passage | TydiQA Closed-book | Codex-Eval Pass@1 | Codex-Eval Pass@10 | AlpacaFarm vs Davinci-003 | Average |
 |:-----------:|:-----------:|:----------:|:-------:|:----------:|:-------:|:-------------------:|:------------------:|:-----------------:|:------------------:|:-------------------------:|---------|
-| 30.3 | 32.3 | 4.5 | 9.0 | 33.6 | 29.6 | 40.4 | 9.3 | 8.6 | 13.4 | 6.8 | 18.7 |
 If you use this model, please cite our work, the llama paper, and the original dataset:

 | MMLU 0-shot | MMLU 5-shot | GSM Direct | GSM CoT | BBH Direct | BBH CoT | TydiQA Gold-Passage | TydiQA Closed-book | Codex-Eval Pass@1 | Codex-Eval Pass@10 | AlpacaFarm vs Davinci-003 | Average |
 |:-----------:|:-----------:|:----------:|:-------:|:----------:|:-------:|:-------------------:|:------------------:|:-----------------:|:------------------:|:-------------------------:|---------|
+| 49.8 | 50.8 | 2.5 | 4.0 | 38.3 | 2.8 | 51.4 | 10.4 | 8.2 | 13.1 | 6.2 | 20.3 |
 If you use this model, please cite our work, the llama paper, and the original dataset: