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README.md
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@@ -51,6 +51,17 @@ Zamba2-2.7B-Instruct punches dramatically above its weight, achieving extremely
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<img src="https://cdn-uploads.huggingface.co/production/uploads/64e40335c0edca443ef8af3e/wXFMLXZA2-xz2PDyUMwTI.png" width="600"/>
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Moreover, due to its unique hybrid SSM architecture, Zamba2-2.7B-Instruct achieves extremely low inference latency and rapid generation with a significantly smaller memory footprint than comparable transformer based models.
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Time to First Token (TTFT) | Output Generation
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<img src="https://cdn-uploads.huggingface.co/production/uploads/64e40335c0edca443ef8af3e/wXFMLXZA2-xz2PDyUMwTI.png" width="600"/>
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| Model | MT-Bench | IFEval
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|-------------|-----|----|---------------|--------------|
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| **Zamba2-2.6B-Instruct** | 2.6B | **72.40** | **53.96** |
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| Mistral-7B-Instruct | 7B | 72.40 | 66.4 | 45.3 |
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| Gemma2-2B-Instruct | 2.7B | 51.69 | 48.8 |
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| H2O-Danube-4B-Chat | 4B | 52.57 | 45.44 |
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| StableLM-Zephyr-3B | 3B | 66.43 | 36.83 |
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Moreover, due to its unique hybrid SSM architecture, Zamba2-2.7B-Instruct achieves extremely low inference latency and rapid generation with a significantly smaller memory footprint than comparable transformer based models.
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Time to First Token (TTFT) | Output Generation
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