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--- |
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library_name: transformers |
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tags: |
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- mergekit |
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- merge |
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license: llama2 |
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--- |
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 |
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# What is this |
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My experiment. Continuation of [Benchmaxxxer series](https://huggingface.co/ChuckMcSneed/BenchmaxxxerPS-v1-123b) (meme models), but a bit more serious. Performs high on my benchmark and on huggingface benchmark, moderately-high in practice. Worth trying? Yeah. It is on the **gooder** side. |
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# Observations |
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* GPTslop: medium-low. Avoid at all costs or it won't stop generating it though. |
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* Writing style: difficult to describe. Not the usual stuff. A bit of an autopilot like thing, if you write your usual lazy "ahh ahh mistress" it can give you a whole page of good text in return. High. |
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* Censorship: if you can handle Xwin, you can handle this model. Medium. |
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* Optimism: medium-low. |
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* Violence: medium-low. |
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* Intelligence: medium. |
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* Creativity: medium-high. |
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* Doesn't like high temperature. Keep below 1.5. |
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# Prompt format |
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Vicuna or Alpaca. |
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## Merge Details |
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). |
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This model was merged using the [linear](https://arxiv.org/abs/2203.05482) merge method. |
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### Models Merged |
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The following models were included in the merge: |
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* [WinterGoddess](https://huggingface.co/Sao10K/WinterGoddess-1.4x-70B-L2) |
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* [WizardLM](https://huggingface.co/WizardLM/WizardLM-70B-V1.0) |
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* [Spicyboros](https://huggingface.co/jondurbin/spicyboros-70b-2.2) |
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* [Euryale](https://huggingface.co/Sao10K/Euryale-1.3-L2-70B) |
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* [Xwin](https://huggingface.co/Xwin-LM/Xwin-LM-70B-V0.1) |
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* [Dolphin](https://huggingface.co/cognitivecomputations/dolphin-2.2-70b) |
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### Configuration |
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The following YAML configuration was used to produce this model: |
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```yaml |
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models: |
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- model: spicyboros |
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parameters: |
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weight: [0.093732305,0.403220342,0.055438423,0.043830778,0.054189303,0.081136828] |
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- model: xwin |
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parameters: |
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weight: [0.398943486,0.042069007,0.161586088,0.470977297,0.389315704,0.416739102] |
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- model: euryale |
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parameters: |
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weight: [0.061483013,0.079698633,0.043067724,0.00202751,0.132183868,0.36578003] |
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- model: dolphin |
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parameters: |
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weight: [0.427942847,0.391488452,0.442164138,0,0,0.002174793] |
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- model: wizard |
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parameters: |
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weight: [0.017898349,0.083523566,0.297743627,0.175345857,0.071770095,0.134169247] |
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- model: WinterGoddess |
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parameters: |
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weight: [0,0,0,0.30781856,0.352541031,0] |
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merge_method: linear |
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dtype: float16 |
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tokenizer_source: base |
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``` |
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# Benchmarks |
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### NeoEvalPlusN_benchmark |
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[My meme benchmark.](https://huggingface.co/datasets/ChuckMcSneed/NeoEvalPlusN_benchmark) |
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|Name |B |C |D |S |P |total|BCD|SP | |
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|-------------------------------------------|---|---|---|----|----|-----|---|-----| |
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|ChuckMcSneed/PMaxxxer-v1-70b |3 |1 |1 |6.75|4.75|16.5 |5 |11.5 | |
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|ChuckMcSneed/SMaxxxer-v1-70b |2 |1 |0 |7.25|4.25|14.5 |3 |11.5 | |
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|ChuckMcSneed/ArcaneEntanglement-model64-70b|3 |2 |1 |7.25|6 |19.25|6 |13.25| |
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Absurdly high. That's what happens when you optimize the merges for a benchmark. |
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### Open LLM Leaderboard Evaluation Results |
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[Leaderboard on Huggingface](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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|Model |Average |ARC |HellaSwag|MMLU |TruthfulQA|Winogrande|GSM8K | |
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|-------------------------------------------|---------|---------|---------|---------|----------|----------|------| |
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|ChuckMcSneed/ArcaneEntanglement-model64-70b|**72.79**|**71.42**|87.96 |**70.83**|60.53 |**83.03** |**63**| |
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|ChuckMcSneed/PMaxxxer-v1-70b |72.41 |71.08 |87.88 |70.39 |59.77 |82.64 |62.7 | |
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|ChuckMcSneed/SMaxxxer-v1-70b |72.23 |70.65 |**88.02**|70.55 |**60.7** |82.87 |60.58 | |
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This model is simply superior to my other meme models here. |