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README.md
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base_model: meta-llama/Llama-3.3-70B-Instruct
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This is a quantization of the [Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama
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The Meta Llama 3.3 is a state-of-the-art multilingual large language model (LLM) with 70 billion parameters, pretrained and instruction-tuned for exceptional performance in generative text-based tasks. Optimized for multilingual dialogue, it supports English and seven additional languages: French, German, Hindi, Italian, Portuguese, Spanish, and Thai, enabling seamless communication across diverse audiences. The model consistently outperforms both open-source and proprietary chat models on key industry benchmarks, delivering superior quality, safety, and helpfulness. Its advanced features and multilingual support position Llama 3.3 as a powerful tool for building innovative AI applications.
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## Evaluations
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This model provides an accuracy recovery of 99.67%.
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| __English__ | __[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama
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| Avg. | 74.1
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| Arc | 71.7
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| Hellaswag | 76.5
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| __French__ | __[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama
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| Avg. | 73.07
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| Arc | 64.7
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| Hellaswag | 76.6
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| MMLU | 77.9
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| __German__ | __[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama
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| Avg. | 70.07
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| Arc | 61.8
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| Hellaswag | 71.2
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| MMLU | 77.2
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| __Italian__ | __[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama
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| Avg. | 73.67
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| Arc | 66.5
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| Hellaswag | 76.0
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| MMLU | 78.5
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| __Portuguese__ | __[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama
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| Avg. | 74.4
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| Arc | 66.4
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| Hellaswag | 77.2
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| MMLU | 79.6
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| __Spanish__ | __[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama
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| Avg. |
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| Arc |
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| Hellaswag |
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| MMLU |
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We did not check for data contamination.
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Evaluation was done using [Eval. Harness](https://github.com/EleutherAI/lm-evaluation-harness) with `limit=1000`.
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base_model: meta-llama/Llama-3.3-70B-Instruct
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---
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This is a quantization of the [Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct).
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The Meta Llama 3.3 is a state-of-the-art multilingual large language model (LLM) with 70 billion parameters, pretrained and instruction-tuned for exceptional performance in generative text-based tasks. Optimized for multilingual dialogue, it supports English and seven additional languages: French, German, Hindi, Italian, Portuguese, Spanish, and Thai, enabling seamless communication across diverse audiences. The model consistently outperforms both open-source and proprietary chat models on key industry benchmarks, delivering superior quality, safety, and helpfulness. Its advanced features and multilingual support position Llama 3.3 as a powerful tool for building innovative AI applications.
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## Evaluations
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This model provides an accuracy recovery of 99.67%.
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| __English__ | __[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct)__ | __[Llama-3.3-70B-Instruct-FP8-Dynamic (this)](https://huggingface.co/cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic)__ |
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| Avg. | 74.1 | 73.75 |
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| Arc | 71.7 | 71.6 |
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| Hellaswag | 76.5 | 75.9 |
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| __French__ | __[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct)__ | __[Llama-3.3-70B-Instruct-FP8-Dynamic (this)](https://huggingface.co/cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic)__ |
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| Avg. | 73.07 | 72.87 |
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| Arc | 64.7 | 64.5 |
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| Hellaswag | 76.6 | 76.6 |
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| MMLU | 77.9 | 77.5 |
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| __German__ | __[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct)__ | __[Llama-3.3-70B-Instruct-FP8-Dynamic (this)](https://huggingface.co/cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic)__ |
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| Avg. | 70.07 | 69.83 |
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| Arc | 61.8 | 61.2 |
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| Hellaswag | 71.2 | 71.1 |
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| MMLU | 77.2 | 77.2 |
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| __Italian__ | __[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct)__ | __[Llama-3.3-70B-Instruct-FP8-Dynamic (this)](https://huggingface.co/cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic)__ |
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| Avg. | 73.67 | 73.37 |
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| Arc | 66.5 | 65.7 |
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| Hellaswag | 76.0 | 76.2 |
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| MMLU | 78.5 | 78.2 |
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| __Portuguese__ | __[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct)__ | __[Llama-3.3-70B-Instruct-FP8-Dynamic (this)](https://huggingface.co/cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic)__ |
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| Avg. | 74.4 | 73.87 |
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| Arc | 66.4 | 65.5 |
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| Hellaswag | 77.2 | 76.9 |
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| MMLU | 79.6 | 79.2 |
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| __Spanish__ | __[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct)__ | __[Llama-3.3-70B-Instruct-FP8-Dynamic (this)](https://huggingface.co/cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic)__ |
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| Avg. | 74 | 74.13 |
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| Arc | 65.8 | 65.8 |
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| Hellaswag | 77.1 | 77.2 |
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| MMLU | 79.1 | 79.4 |
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We did not check for data contamination.
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Evaluation was done using [Eval. Harness](https://github.com/EleutherAI/lm-evaluation-harness) with `limit=1000`.
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