license: mit
tags:
- generated_from_trainer
- rag
- ner
- parse
- summary
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.
Special Thanks to https://nationtech.io/ for their generous sponorship in training this model.
This model is a fine-tuned version of 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.
This model usses:
<|system|>
<|user|>
<|assistant|>
<|function_list|>
<|function_call|>
<|function_response|>
<|data|>
<|summary|>
<|tag|>
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
Detailed results can be found here
| 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 |