pravdin/hermes-2-pro-mistral-7b-mistral-7b-instruct-v0.3-linear-merge-gguf overview

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    "license": "apache-2.0",
    "tags": [
      "merge",
      "mergekit",
      "lazymergekit",
      "NousResearch/Hermes-2-Pro-Mistral-7B",
      "mistralai/Mistral-7B-Instruct-v0.3"
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    "frontmatter": {
      "license": "apache-2.0",
      "tags": [
        "merge",
        "mergekit",
        "lazymergekit",
        "NousResearch/Hermes-2-Pro-Mistral-7B",
        "mistralai/Mistral-7B-Instruct-v0.3"
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    "summary": "Hermes-2-Pro-Mistral-7B-Mistral-7B-Instruct-v0.3-linear-merge is a merge of the following models using mergekit: * NousResearch/Hermes-2-Pro-Mistral-7B * mistralai/Mistral-7B-Instruct-v0.3",
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    "readme_markdown": "---\nlicense: apache-2.0\ntags:\n- merge\n- mergekit\n- lazymergekit\n- NousResearch/Hermes-2-Pro-Mistral-7B\n- mistralai/Mistral-7B-Instruct-v0.3\n---\n# Quantized GGUF model Hermes-2-Pro-Mistral-7B-Mistral-7B-Instruct-v0.3-linear-merge\nThis model has been quantized using llama-quantize from [llama.cpp](https://github.com/ggerganov/llama.cpp)\n    \n\n# Hermes-2-Pro-Mistral-7B-Mistral-7B-Instruct-v0.3-linear-merge\n\nHermes-2-Pro-Mistral-7B-Mistral-7B-Instruct-v0.3-linear-merge is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):\n* [NousResearch/Hermes-2-Pro-Mistral-7B](https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B)\n* [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3)\n\n## 🧩 Merge Configuration\n\n```yaml\nmerge_method: linear\nbase_model: mistralai/Mistral-7B-Instruct-v0.3\nmodels:\n  - model: NousResearch/Hermes-2-Pro-Mistral-7B\n    parameters:\n      weight: 0.3\n  - model: mistralai/Mistral-7B-Instruct-v0.3\n    parameters:\n      weight: 0.7\nparameters:\n  normalize: true\ndtype: float16\n```\n\n## Model Description\n\nThe Hermes-2-Pro-Mistral-7B-Mistral-7B-Instruct-v0.3-linear-merge combines the advanced conversational capabilities of the Hermes 2 Pro model with the instruction-following prowess of the Mistral-7B-Instruct model. This strategic fusion aims to enhance the model's ability to understand and generate contextually relevant responses while maintaining a high level of performance across various natural language processing tasks.\n\nHermes 2 Pro is an upgraded version of the original Nous Hermes 2, featuring a refined dataset and improved function calling capabilities. It excels in generating structured outputs, making it particularly useful for applications requiring precise data formatting, such as JSON responses. The Mistral-7B-Instruct model, on the other hand, is designed to follow instructions effectively, making it a strong candidate for tasks that require adherence to user prompts.\n\n## Use Cases\n\nThis merged model is well-suited for a variety of applications, including but not limited to:\n- Conversational agents and chatbots\n- Function calling and structured data generation\n- Instruction-based tasks and question answering\n- Creative writing and storytelling\n\n## Model Features\n\n- **Enhanced Conversational Abilities**: The model leverages the conversational strengths of Hermes 2 Pro, allowing for engaging and context-aware dialogues.\n- **Instruction Following**: With the integration of Mistral-7B-Instruct, the model can effectively follow user instructions, making it ideal for task-oriented applications.\n- **Function Calling and JSON Outputs**: The model supports advanced function calling and can generate structured JSON outputs, facilitating integration with various applications and APIs.\n\n## Evaluation Results\n\nThe performance of the parent models provides a solid foundation for the merged model. Here are some evaluation metrics from the original models:\n\n### Hermes 2 Pro\n- **Function Calling Accuracy**: 91%\n- **JSON Mode Accuracy**: 84%\n\n### Mistral-7B-Instruct\nWhile specific evaluation metrics for Mistral-7B-Instruct were not available, it is known for its strong instruction-following capabilities, which contribute to the overall performance of the merged model.\n\n## Limitations\n\nDespite the strengths of the merged model, it may inherit some limitations from its parent models. Potential issues include:\n- **Biases**: The model may reflect biases present in the training data of both parent models, which could affect the fairness and neutrality of its outputs.\n- **Contextual Understanding**: While the model excels in many areas, there may still be challenges in understanding highly nuanced or ambiguous prompts.\n\nIn summary, the Hermes-2-Pro-Mistral-7B-Mistral-7B-Instruct-v0.3-linear-merge represents a powerful tool for a wide range of NLP tasks, combining the best features of its parent models while also carrying forward some of their limitations.",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "merge",
    "mergekit",
    "lazymergekit",
    "NousResearch/Hermes-2-Pro-Mistral-7B",
    "mistralai/Mistral-7B-Instruct-v0.3",
    "license:apache-2.0",
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    "region:us",
    "conversational"
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  "last_modified": "2024-08-21T06:35:40.000Z",
  "created_at": "2024-08-21T05:42:11.000Z",
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