--- license: mit tags: - generated_from_trainer base_model: Josephgflowers/TinyLlama-Cinder-Tiny-Agent model-index: - name: TinyLlama-Cinder-Agent-v1 results: [] --- The goal of this Model is to build a Tinyllama model that can be used for tool usage, RAG, take system instructions, and as a general assistant. This model is a fine-tuned version of [Josephgflowers/TinyLlama-Cinder-Tiny-Agent](https://huggingface.co/Josephgflowers/TinyLlama-Cinder-Tiny-Agent). Special Thanks to https://nationtech.io/ for their generous sponorship in training this model. ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6328952f798f8d122ce62a44/MbN_SXChmMxuHO8GjdUSc.png) This model is a fine-tuned version of [Josephgflowers/TinyLlama-3T-Cinder-v1.2](https://huggingface.co/Josephgflowers/TinyLlama-3T-Cinder-v1.2) on https://huggingface.co/datasets/Josephgflowers/agent_1. ## Model description This models is trained for RAG, Summary, Function Calling and Tool usage. Trained off of Cinder. Cinder is a chatbot designed for chat about STEM topics and storytelling. More information coming. See https://huggingface.co/Josephgflowers/TinyLlama-Cinder-Agent-Rag/blob/main/tinyllama_agent_cinder_txtai-rag.py For usage example with wiki rag. # [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_Josephgflowers__TinyLlama-Cinder-Agent-v1) | Metric |Value| |---------------------------------|----:| |Avg. |39.17| |AI2 Reasoning Challenge (25-Shot)|34.90| |HellaSwag (10-Shot) |53.87| |MMLU (5-Shot) |26.89| |TruthfulQA (0-shot) |39.08| |Winogrande (5-shot) |59.12| |GSM8k (5-shot) |21.15| # [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_Josephgflowers__TinyLlama-Cinder-Agent-v1) | Metric |Value| |-------------------|----:| |Avg. | 5.82| |IFEval (0-Shot) |26.70| |BBH (3-Shot) | 3.80| |MATH Lvl 5 (4-Shot)| 0.38| |GPQA (0-shot) | 0.00| |MuSR (0-shot) | 2.23| |MMLU-PRO (5-shot) | 1.79|