Unveiling MistralOrca: A Leap Towards Open-Source AI Excellence

In recent times, the realm of open-source AI has seen a monumental stride towards excellence with the advent of MistralOrca. This innovative model emerged from a collaboration that aimed to push the boundaries of what moderate consumer GPUs can achieve.

The narrative began with the meticulous creation of the OpenOrca dataset, a notable endeavor to replicate the dataset heralded in Microsoft Research's Orca Paper. The Alignment Lab team, known for their avant-garde approach, fine-tuned Mistral 7B using this dataset, employing OpenChat packing and Axolotl for training. The result? A release that boasts of GPT-4 augmented data finesse, a trait shared with its sibling model, OpenOrcaxOpenChat-Preview2-13B.

As of its release, MistralOrca carved its niche as the second-best model among those with a size less than 30B on the HF Leaderboard, outclassing all but one 13B model. This wasn't just a release; it was a statement of capability, a fully open model showcasing class-breaking performance, all while being accessible on moderate consumer GPUs. A tip of the hat to the Mistral team for pioneering this trail.

MistralOrca is not just a name; it's a testament to the seamless meld between robust technology and the open-source ethos. Want to give it a whirl? It's running on fast GPUs unquantized for an unparalleled user experience. You can find it [here](https://huggingface.co/spaces/Open-Orca/Mistral-7B-OpenOrca).

Beyond just a model, the team has provided a visual feast for data enthusiasts. Explore the full (pre-filtering) dataset on their Nomic Atlas Map, an endeavor to offer transparency and insights into the data that powers MistralOrca.

Now, for those who are on the lookout for quantized models, TheBloke has generously facilitated quantized versions of MistralOrca. Whether it's AWQ, GPTQ, or GGUF, a new horizon of exploration awaits [here](https://huggingface.co/TheBloke/Mistral-7B-OpenOrca-AWQ).

The tale doesn't end here; the ongoing journey sees the Alignment Lab in the throes of training more models, with the promise of exciting partnerships on the horizon. Stay tuned for sneak-peak announcements on their [Discord](https://AlignmentLab.ai), or delve deeper into the Axolotl trainer on the [OpenAccess AI Collective Discord](https://discord.gg/5y8STgB3P3).

The performance metrics of MistralOrca are nothing short of stellar. With a 105% performance of the base model on HF Leaderboard evaluations, it transcends the performance of all 7B models and all but one 13B model, averaging a score of 65.33. These evaluations were meticulously carried out using the Language Model Evaluation Harness, mirroring the HuggingFace LLM Leaderboard version.

The comparative analysis with the base Mistral-7B model unveils a 129% performance on AGI Eval, averaging 0.397, and a 119% performance on BigBench-Hard, averaging 0.416. These figures aren’t just digits; they are a testament to the colossal strides MistralOrca has made in the field.

The training regime was no less rigorous. Utilizing 8x A6000 GPUs for a marathon 62-hour training run, the team completed 4 epochs of full fine-tuning on their dataset. The commodity cost stood at a modest ~$400, a small price for a giant leap in open-source AI excellence.

In conclusion, MistralOrca isn’t merely a model; it’s a milestone in the open-source AI narrative. It epitomizes what collaborative effort, coupled with cutting-edge technology, can achieve. As the AI community waits with bated breath for what's next from Alignment Lab, MistralOrca stands as a beacon of what’s possible in the ever-evolving world of Artificial Intelligence.

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