transformers safetensors mixtral text-generation moe frankenmoe merge mergekit Himitsui/Kaiju-11B Sao10K/Fimbulvetr-11B-v2 decapoda-research/Antares-11b-v2 beberik/Nyxene-v3-11B conversational base_model:Himitsui/Kaiju-11B base_model:Sao10K/Fimbulvetr-11B-v2 base_model:decapoda-research/Antares-11b-v2 base_model:beberik/Nyxene-v3-11B license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- Himitsui/Kaiju-11B
- Sao10K/Fimbulvetr-11B-v2
- decapoda-research/Antares-11b-v2
- beberik/Nyxene-v3-11B
base_model:
- Himitsui/Kaiju-11B
- Sao10K/Fimbulvetr-11B-v2
- decapoda-research/Antares-11b-v2
- beberik/Nyxene-v3-11B
model-index:
- name: Umbra-v3-MoE-4x11b
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 68.43
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Umbra-v3-MoE-4x11b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 87.83
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Umbra-v3-MoE-4x11b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 65.99
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Umbra-v3-MoE-4x11b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 69.3
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Umbra-v3-MoE-4x11b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 83.9
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Umbra-v3-MoE-4x11b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 63.08
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Umbra-v3-MoE-4x11b
      name: Open LLM Leaderboard
---


ExllamaV2 version of the model created by [Steelskull](https://huggingface.co/Steelskull)!

Original Model https://huggingface.co/Steelskull/Umbra-v3-MoE-4x11b

calibration dataset [here.](https://huggingface.co/datasets/royallab/PIPPA-cleaned)

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

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<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Umbra-v3-MoE-4x11b Data Card</title>
    <link href="https://fonts.googleapis.com/css2?family=Quicksand:wght@400;500;600&display=swap" rel="stylesheet">
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<body>
<div class="container">
    <div class="header">
        <h1>Umbra-v3-MoE-4x11b</h1>
    </div>
    <div class="info">
        <img src="https://cdn-uploads.huggingface.co/production/uploads/64545af5ec40bbbd01242ca6/MHmVGOLGh4I5MfQ83iiXS.jpeg">
        <p><strong>Creator:</strong> <a href="https://huggingface.co/Steelskull" target="_blank">SteelSkull</a></p>
        <p><strong>About Umbra-v3-MoE-4x11b:</strong> A Mixture of Experts model designed for general assistance with a special knack for storytelling and RP/ERP</p>
        <p>Integrates models from notable sources for enhanced performance in diverse tasks.</p>
        <p><strong>Source Models:</strong></p>
        <ul>
            <li><a href="https://huggingface.co/Himitsui/Kaiju-11B">Himitsui/Kaiju-11B</a></li>
            <li><a href="https://huggingface.co/Sao10K/Fimbulvetr-11B-v2">Sao10K/Fimbulvetr-11B-v2</a></li>
            <li><a href="https://huggingface.co/decapoda-research/Antares-11b-v2">decapoda-research/Antares-11b-v2</a></li>
            <li><a href="https://huggingface.co/beberik/Nyxene-v3-11B">beberik/Nyxene-v3-11B</a></li>
        </ul>
    </div>
    <div class="update-section">
        <h2>Update-Log:</h2>
        <p>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.</p>
        <p><strong>What's Fresh in v3?</strong></p>
        <p>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".</p>
        <p><strong>Negative Prompt Minimalism</strong></p>
        <p>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.</p>
        <p><strong>Still Guessing, Aren’t We?</strong></p>
        <p>Just so we're clear, "v3" is not the messiah of updates. It’s another experiment in the saga.</p>
        <p>Dive into Umbra v3 and toss your two cents my way. Your feedback is the caffeine in my code marathon.</p>
    </div>
</div>
</body>
</html>
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Steelskull__Umbra-v3-MoE-4x11b)

|             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|

