--- language: - en license: apache-2.0 tags: - mistral - not-for-all-audiences - merge pipeline_tag: text-generation inference: false model-index: - name: DarkSapling-7B-v2.0 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: 64.16 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/DarkSapling-7B-v2.0 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: 85.1 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/DarkSapling-7B-v2.0 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: 64.37 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/DarkSapling-7B-v2.0 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: 52.21 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/DarkSapling-7B-v2.0 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: 78.61 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/DarkSapling-7B-v2.0 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: 45.41 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/DarkSapling-7B-v2.0 name: Open LLM Leaderboard --- # DarkSapling-7B-v2.0 ![image/png](https://huggingface.co/TeeZee/DarkSapling-7B-v2.0/resolve/main/DarkSapling-7B-v2.0.jpg) ## Model Details - A result of 4 models merge. DARE TIES method was used this time so resulting model better preserves characteristics of all included models than v1.x. - models used for merge: [cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser](https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser) [KoboldAI/Mistral-7B-Holodeck-1](https://huggingface.co/KoboldAI/Mistral-7B-Holodeck-1) [KoboldAI/Mistral-7B-Erebus-v3](https://huggingface.co/KoboldAI/Mistral-7B-Erebus-v3) [cognitivecomputations/samantha-mistral-7b](https://huggingface.co/cognitivecomputations/samantha-mistral-7b) - See [mergekit-config.yml](https://huggingface.co/TeeZee/DarkSapling-7B-v2.0/resolve/main/mergekit-config.yml) for details on the merge method used. **Warning: This model can produce NSFW content!** ## Results - a little different than version v1.0, more romantic and empathetic. - smarter than versions 1.0 and 1.1. - best for one-on-one ERP. - produces SFW nad NSFW content without issues, switches context seamlessly. - sticks to character card - pretty smart due to mistral, empathetic after Samantha and sometimes produces dark scenarions - Erebus. - storytelling is satisfactory due to Holodeck - good at following instructions All comments are greatly appreciated, download, test and if you appreciate my work, consider buying me my fuel: Buy Me A Coffee # [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_TeeZee__DarkSapling-7B-v2.0) | Metric |Value| |---------------------------------|----:| |Avg. |64.98| |AI2 Reasoning Challenge (25-Shot)|64.16| |HellaSwag (10-Shot) |85.10| |MMLU (5-Shot) |64.37| |TruthfulQA (0-shot) |52.21| |Winogrande (5-shot) |78.61| |GSM8k (5-shot) |45.41|