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Model: TeeZee/DarkSapling-7B-v1.0 Source: Original Platform
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README.md
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README.md
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---
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language:
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- en
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license: apache-2.0
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tags:
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- mistral
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- not-for-all-audiences
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- merge
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pipeline_tag: text-generation
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inference: false
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model-index:
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- name: DarkSapling-7B-v1.0
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 61.6
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/DarkSapling-7B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 82.59
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/DarkSapling-7B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 62.46
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/DarkSapling-7B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 45.09
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/DarkSapling-7B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 77.19
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/DarkSapling-7B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 40.18
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/DarkSapling-7B-v1.0
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name: Open LLM Leaderboard
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---
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# DarkSapling-7B-v1.0
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## Model Details
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- A result of 4 models merge.
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- models used for merge:
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[cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser](https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser)
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[KoboldAI/Mistral-7B-Holodeck-1](https://huggingface.co/KoboldAI/Mistral-7B-Holodeck-1)
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[KoboldAI/Mistral-7B-Erebus-v3](https://huggingface.co/KoboldAI/Mistral-7B-Erebus-v3)
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[cognitivecomputations/samantha-mistral-7b](https://huggingface.co/cognitivecomputations/samantha-mistral-7b)
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- See [mergekit-config.yml](https://huggingface.co/TeeZee/DarkSapling-7B-v1.0/resolve/main/mergekit-config.yml) for details on the merge method used.
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**Warning: This model can produce NSFW content!**
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## Results
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- produces SFW nad NSFW content without issues, switches context seamlessly.
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- sticks to character card
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- pretty smart due to mistral, empathetic after Samantha and sometimes produces dark scenarions - Erebus.
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- storytelling is satisfactory due to Holodeck
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- good at following instructions
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All comments are greatly appreciated, download, test and if you appreciate my work, consider buying me my fuel:
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<a href="https://www.buymeacoffee.com/TeeZee" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 60px !important;width: 217px !important;" ></a>
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_TeeZee__DarkSapling-7B-v1.0)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |61.52|
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|AI2 Reasoning Challenge (25-Shot)|61.60|
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|HellaSwag (10-Shot) |82.59|
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|MMLU (5-Shot) |62.46|
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|TruthfulQA (0-shot) |45.09|
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|Winogrande (5-shot) |77.19|
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|GSM8k (5-shot) |40.18|
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