ExllamaV2 version of the model created by Steelskull!
Original Model https://huggingface.co/Steelskull/Umbra-v3-MoE-4x11b
calibration dataset here.
Requires ExllamaV2, which is being developed by turboderp https://github.com/turboderp/exllamav2 under an MIT license.
Test using 4096 measurement length and rp dataset. Perplexity came out to an 8 vs the Wiki which was at a 6. Haven't tested enough to tell if there is much difference in practice between the two.
Branch is 8b8h using wikitext at 4096 length
Umbra-v3-MoE-4x11b
Creator: SteelSkull
About Umbra-v3-MoE-4x11b: A Mixture of Experts model designed for general assistance with a special knack for storytelling and RP/ERP
Integrates models from notable sources for enhanced performance in diverse tasks.
Source Models:
Update-Log:
The [Umbra Series] keeps rolling out from the [Lumosia Series] garage, aiming to be your digital Alfred with a side of Shakespeare for those RP/ERP nights.
What's Fresh in v3?
Didn’t reinvent the wheel, just slapped on some fancier rims. Upgraded the models and tweaked the prompts a bit. Now, Umbra's not just a general use LLM; it's also focused on spinning stories and "Stories".
Negative Prompt Minimalism
Got the prompts to do a bit of a diet and gym routine—more beef on the positives, trimming down the negatives as usual with a dash of my midnight musings.
Still Guessing, Aren’t We?
Just so we're clear, "v3" is not the messiah of updates. It’s another experiment in the saga.
Dive into Umbra v3 and toss your two cents my way. Your feedback is the caffeine in my code marathon.
| Metric | Value |
|---|---|
| Avg. | 73.09 |
| AI2 Reasoning Challenge (25-Shot) | 68.43 |
| HellaSwag (10-Shot) | 87.83 |
| MMLU (5-Shot) | 65.99 |
| TruthfulQA (0-shot) | 69.30 |
| Winogrande (5-shot) | 83.90 |
| GSM8k (5-shot) | 63.08 |
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Model tree for AzureBlack/Umbra-v3-MoE-4x11b-exl2-8bpw-8h-rpcal
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard68.430
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard87.830
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard65.990
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard69.300
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard83.900
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard63.080