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+ ---
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+ language:
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+ - en
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+ base_model: Nitral-AI/Poppy_Porpoise-0.85-L3-8B
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+ license: other
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+ model-index:
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+ - name: Poppy_Porpoise-0.85-L3-8B
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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: 63.4
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+ name: normalized accuracy
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+ source:
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+ url: >-
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+ https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Nitral-AI/Poppy_Porpoise-0.85-L3-8B
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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: 82.89
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+ name: normalized accuracy
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+ source:
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+ url: >-
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+ https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Nitral-AI/Poppy_Porpoise-0.85-L3-8B
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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: 68.04
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+ name: accuracy
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+ source:
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+ url: >-
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+ https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Nitral-AI/Poppy_Porpoise-0.85-L3-8B
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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: 54.12
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+ source:
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+ url: >-
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+ https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Nitral-AI/Poppy_Porpoise-0.85-L3-8B
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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: 77.9
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+ name: accuracy
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+ source:
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+ url: >-
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+ https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Nitral-AI/Poppy_Porpoise-0.85-L3-8B
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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: 69.07
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+ name: accuracy
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+ source:
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+ url: >-
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+ https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Nitral-AI/Poppy_Porpoise-0.85-L3-8B
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+ name: Open LLM Leaderboard
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ ---
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+ # Poppy_Porpoise-0.85-L3-8B-GGUF
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+ This is quantized version of [Nitral-AI/Poppy_Porpoise-0.85-L3-8B]() created using llama.cpp
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+
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+ # Model Description
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+ "Poppy Porpoise" is a cutting-edge AI roleplay assistant based on the Llama 3 8B model, specializing in crafting unforgettable narrative experiences. With its advanced language capabilities, Poppy expertly immerses users in an interactive and engaging adventure, tailoring each adventure to their individual preferences.
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+
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+ # Recomended ST Presets:(Updated for 0.85) [Porpoise Presets](https://huggingface.co/Nitral-8B-r1/tree/main/Presets)
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+
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+ If you want to use vision functionality:
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+
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+ * You must use the latest versions of [Koboldcpp](https://github.com/LostRuins/koboldcpp).
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+
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+ # To use the multimodal capabilities of this model and use **vision** you need to load the specified **mmproj** file, this can be found inside this model repo. [Llava MMProj](https://huggingface.co/Nitral-AI/Llama-3-Update-2.0-mmproj-model-f16)
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+
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+ * You can load the **mmproj** by using the corresponding section in the interface:
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+
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/65d4cf2693a0a3744a27536c/UX6Ubss2EPNAT3SKGMLe0.png)
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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_Nitral-AI__Poppy_Porpoise-0.85-L3-8B)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |69.24|
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+ |AI2 Reasoning Challenge (25-Shot)|63.40|
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+ |HellaSwag (10-Shot) |82.89|
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+ |MMLU (5-Shot) |68.04|
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+ |TruthfulQA (0-shot) |54.12|
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+ |Winogrande (5-shot) |77.90|
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+ |GSM8k (5-shot) |69.07|