初始化项目，由ModelHub XC社区提供模型

Model: arcee-ai/Llama-Spark
Source: Original Platform

README.md

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+---
+license: llama3
+---
+<div align="center">
+  <img src="https://i.ibb.co/9hwFrvL/BLMs-Wkx-NQf-W-46-FZDg-ILhg.jpg" alt="Arcee Spark" style="border-radius: 10px; box-shadow: 0 4px 8px 0 rgba(0, 0, 0, 0.2), 0 6px 20px 0 rgba(0, 0, 0, 0.19); max-width: 100%; height: auto;">
+</div>
+
+
+Llama-Spark is a powerful conversational AI model developed by Arcee.ai. It's built on the foundation of Llama-3.1-8B and merges the power of our Tome Dataset with Llama-3.1-8B-Instruct, resulting in a remarkable conversationalist that punches well above its 8B parameter weight class.
+
+## GGUFs available [here](https://huggingface.co/arcee-ai/Llama-Spark-GGUF)
+
+## Model Description
+
+Llama-Spark is our commitment to consistently delivering the best-performing conversational AI in the 6-9B parameter range. As new base models become available, we'll continue to update and improve Spark to maintain its leadership position. 
+
+This model is a successor to our original Arcee-Spark, incorporating advancements and learnings from our ongoing research and development.
+
+## Intended Uses
+
+Llama-Spark is intended for use in conversational AI applications, such as chatbots, virtual assistants, and dialogue systems. It excels at engaging in natural and informative conversations.
+
+## Training Information
+
+Llama-Spark is built upon the Llama-3.1-8B base model, fine-tuned using of the Tome Dataset and merged with Llama-3.1-8B-Instruct.
+
+## Acknowledgements
+
+We extend our deepest gratitude to **PrimeIntellect** for being our compute sponsor for this project. 
+
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_arcee-ai__Llama-Spark)
+
+|      Metric       |Value|
+|-------------------|----:|
+|Avg.               |24.90|
+|IFEval (0-Shot)    |79.11|
+|BBH (3-Shot)       |29.77|
+|MATH Lvl 5 (4-Shot)| 1.06|
+|GPQA (0-shot)      | 6.60|
+|MuSR (0-shot)      | 2.62|
+|MMLU-PRO (5-shot)  |30.23|