richarderkhov/rombodawg_-_everyone-llm-7b-base-gguf overview

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    "summary": "`` | Model                              | Average |   ARC   | HellaSwag |   MMLU  | TruthfulQA | Winogrande |  GSM8K  | |------------------------------------|---------|---------|-----------|---------|------------|------------|---------| |   rombodawg/Everyone-LLM-7b-Base   | 70.21   | 66.38   | 86.02     | 64.94   | 57.89      | 80.43      | 65.58   | ` Config for the merger can be found bellow: `yaml models: parameters: weight: 1 parameters: weight: 1 parameters: weight: 1 parameters: weight: 1 parameters: weight: 1 parameters: weight: 1 parameters: weight: 1 parameters: weight: 1 parameters: weight: 1 parameters: weight: 1 parameters: weight: 1 parameters: weight: 1 parameters: weight: 1 parameters: weight: 1 merge_method: task_arithmetic base_model: mistralai_Mistral-7B-v0.1 parameters: normalize: true int8_mask: true dtype: float16 `` # Open LLM Leaderboard Evaluation Results Detailed results can be found here |             Metric              |Value| |---------------------------------|----:| |Avg.                             |70.21| |AI2 Reasoning Challenge (25-Shot)|66.38| |HellaSwag (10-Shot)              |86.02| |MMLU (5-Shot)                    |64.94| |TruthfulQA (0-shot)              |57.89| |Winogrande (5-shot)              |80.43| |GSM8k (5-shot)                   |65.58|",
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    "readme_markdown": "Quantization made by Richard Erkhov.\n\n[Github](https://github.com/RichardErkhov)\n\n[Discord](https://discord.gg/pvy7H8DZMG)\n\n[Request more models](https://github.com/RichardErkhov/quant_request)\n\n\nEveryone-LLM-7b-Base - GGUF\n- Model creator: https://huggingface.co/rombodawg/\n- Original model: https://huggingface.co/rombodawg/Everyone-LLM-7b-Base/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [Everyone-LLM-7b-Base.Q2_K.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q2_K.gguf) | Q2_K | 2.53GB |\n| [Everyone-LLM-7b-Base.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.IQ3_XS.gguf) | IQ3_XS | 2.81GB |\n| [Everyone-LLM-7b-Base.IQ3_S.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.IQ3_S.gguf) | IQ3_S | 2.96GB |\n| [Everyone-LLM-7b-Base.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q3_K_S.gguf) | Q3_K_S | 2.95GB |\n| [Everyone-LLM-7b-Base.IQ3_M.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.IQ3_M.gguf) | IQ3_M | 3.06GB |\n| [Everyone-LLM-7b-Base.Q3_K.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q3_K.gguf) | Q3_K | 3.28GB |\n| [Everyone-LLM-7b-Base.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q3_K_M.gguf) | Q3_K_M | 3.28GB |\n| [Everyone-LLM-7b-Base.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q3_K_L.gguf) | Q3_K_L | 3.56GB |\n| [Everyone-LLM-7b-Base.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.IQ4_XS.gguf) | IQ4_XS | 3.67GB |\n| [Everyone-LLM-7b-Base.Q4_0.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q4_0.gguf) | Q4_0 | 3.83GB |\n| [Everyone-LLM-7b-Base.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.IQ4_NL.gguf) | IQ4_NL | 3.87GB |\n| [Everyone-LLM-7b-Base.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q4_K_S.gguf) | Q4_K_S | 3.86GB |\n| [Everyone-LLM-7b-Base.Q4_K.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q4_K.gguf) | Q4_K | 4.07GB |\n| [Everyone-LLM-7b-Base.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q4_K_M.gguf) | Q4_K_M | 4.07GB |\n| [Everyone-LLM-7b-Base.Q4_1.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q4_1.gguf) | Q4_1 | 4.24GB |\n| [Everyone-LLM-7b-Base.Q5_0.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q5_0.gguf) | Q5_0 | 4.65GB |\n| [Everyone-LLM-7b-Base.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q5_K_S.gguf) | Q5_K_S | 4.65GB |\n| [Everyone-LLM-7b-Base.Q5_K.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q5_K.gguf) | Q5_K | 4.78GB |\n| [Everyone-LLM-7b-Base.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q5_K_M.gguf) | Q5_K_M | 4.78GB |\n| [Everyone-LLM-7b-Base.Q5_1.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q5_1.gguf) | Q5_1 | 5.07GB |\n| [Everyone-LLM-7b-Base.Q6_K.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q6_K.gguf) | Q6_K | 5.53GB |\n| [Everyone-LLM-7b-Base.Q8_0.gguf](https://huggingface.co/RichardErkhov/rombodawg_-_Everyone-LLM-7b-Base-gguf/blob/main/Everyone-LLM-7b-Base.Q8_0.gguf) | Q8_0 | 7.17GB |\n\n\n\n\nOriginal model description:\n---\nlicense: unknown\ntags:\n- merge\nmodel-index:\n- name: Everyone-LLM-7b-Base\n  results:\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: AI2 Reasoning Challenge (25-Shot)\n      type: ai2_arc\n      config: ARC-Challenge\n      split: test\n      args:\n        num_few_shot: 25\n    metrics:\n    - type: acc_norm\n      value: 66.38\n      name: normalized accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rombodawg/Everyone-LLM-7b-Base\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: HellaSwag (10-Shot)\n      type: hellaswag\n      split: validation\n      args:\n        num_few_shot: 10\n    metrics:\n    - type: acc_norm\n      value: 86.02\n      name: normalized accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rombodawg/Everyone-LLM-7b-Base\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: MMLU (5-Shot)\n      type: cais/mmlu\n      config: all\n      split: test\n      args:\n        num_few_shot: 5\n    metrics:\n    - type: acc\n      value: 64.94\n      name: accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rombodawg/Everyone-LLM-7b-Base\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: TruthfulQA (0-shot)\n      type: truthful_qa\n      config: multiple_choice\n      split: validation\n      args:\n        num_few_shot: 0\n    metrics:\n    - type: mc2\n      value: 57.89\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rombodawg/Everyone-LLM-7b-Base\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: Winogrande (5-shot)\n      type: winogrande\n      config: winogrande_xl\n      split: validation\n      args:\n        num_few_shot: 5\n    metrics:\n    - type: acc\n      value: 80.43\n      name: accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rombodawg/Everyone-LLM-7b-Base\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: GSM8k (5-shot)\n      type: gsm8k\n      config: main\n      split: test\n      args:\n        num_few_shot: 5\n    metrics:\n    - type: acc\n      value: 65.58\n      name: accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rombodawg/Everyone-LLM-7b-Base\n      name: Open LLM Leaderboard\n---\nEveryone-LLM-7b-Base\n\n\n![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/642cc1c253e76b4c2286c58e/ECrHQnZnv8UM9GUCQtlWW.jpeg)\n\nEveryoneLLM series of models made by the community, for the community.\n\nThis is the first version of Everyone-LLM, a model that combines the power of the large majority of powerfull fine-tuned LLM's made by the community, to create a vast and knowledgable LLM with various abilities.\n\n\nPrompt template: Alpaca\n```\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\n### Instruction:\n{prompt}\n### Response:\n```\n\nThe models that were used in this merger were as follow:\n\n- https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b-dpo\n\n- https://huggingface.co/jondurbin/bagel-dpo-7b-v0.4\n\n- https://huggingface.co/Locutusque/Hercules-2.0-Mistral-7B\n\n\n- https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca\n\n- https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B\n\n- https://huggingface.co/NousResearch/Nous-Capybara-7B-V1.9\n\n- https://huggingface.co/Intel/neural-chat-7b-v3-3\n\n- https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2\n\n- https://huggingface.co/senseable/WestLake-7B-v2\n\n- https://huggingface.co/defog/sqlcoder-7b\n\n- https://huggingface.co/meta-math/MetaMath-Mistral-7B\n\n- https://huggingface.co/nextai-team/apollo-v1-7b\n\n- https://huggingface.co/WizardLM/WizardMath-7B-V1.1\n\n- https://huggingface.co/openchat/openchat-3.5-0106\n\n- https://huggingface.co/mistralai/Mistral-7B-v0.1\n\nThank you to the creators of the above ai models, they have full credit for the EveryoneLLM series of models. Without their hard work we wouldnt be able to achieve the great success we have in the open source community. 💗\n\nYou can find the write up for merging models here:\n\nhttps://docs.google.com/document/d/1_vOftBnrk9NRk5h10UqrfJ5CDih9KBKL61yvrZtVWPE/edit?usp=sharing\n\n\n# Open LLM Leaderboard Scores\n```\n| Model                              | Average |   ARC   | HellaSwag |   MMLU  | TruthfulQA | Winogrande |  GSM8K  |\n|------------------------------------|---------|---------|-----------|---------|------------|------------|---------|\n|   rombodawg/Everyone-LLM-7b-Base   | 70.21   | 66.38   | 86.02     | 64.94   | 57.89      | 80.43      | 65.58   |\n```\n\nConfig for the merger can be found bellow:\n\n```yaml\nmodels:\n  - model: cognitivecomputations_dolphin-2.6-mistral-7b-dpo\n    parameters:\n      weight: 1\n  - model: jondurbin_bagel-dpo-7b-v0.4\n    parameters:\n      weight: 1\n  - model: Locutusque_Hercules-2.0-Mistral-7B\n    parameters:\n      weight: 1\n  - model: Open-Orca_Mistral-7B-OpenOrca\n    parameters:\n      weight: 1\n  - model: teknium_OpenHermes-2.5-Mistral-7B\n    parameters:\n      weight: 1\n  - model: NousResearch_Nous-Capybara-7B-V1.9\n\n    parameters:\n      weight: 1\n  - model: Intel_neural-chat-7b-v3-3\n    parameters:\n      weight: 1\n  - model: mistralai_Mistral-7B-Instruct-v0.2\n    parameters:\n      weight: 1\n  - model: senseable_WestLake-7B-v2\n    parameters:\n      weight: 1\n  - model: defog_sqlcoder-7b\n    parameters:\n      weight: 1\n  - model: meta-math_MetaMath-Mistral-7B\n    parameters:\n      weight: 1\n  - model: nextai-team_apollo-v1-7b\n    parameters:\n      weight: 1\n  - model: WizardLM_WizardMath-7B-V1.1\n    parameters:\n      weight: 1\n  - model: openchat_openchat-3.5-0106\n    parameters:\n      weight: 1\nmerge_method: task_arithmetic\nbase_model: mistralai_Mistral-7B-v0.1\nparameters:\n  normalize: true\n  int8_mask: true\ndtype: float16\n\n```\n\n# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)\nDetailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_rombodawg__Everyone-LLM-7b-Base)\n\n|             Metric              |Value|\n|---------------------------------|----:|\n|Avg.                             |70.21|\n|AI2 Reasoning Challenge (25-Shot)|66.38|\n|HellaSwag (10-Shot)              |86.02|\n|MMLU (5-Shot)                    |64.94|\n|TruthfulQA (0-shot)              |57.89|\n|Winogrande (5-shot)              |80.43|\n|GSM8k (5-shot)                   |65.58|\n\n\n\n",
    "related_quantizations": []
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