Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Josephgflowers/Tinyllama-Cinder-Agent-v1-GGUF# Run inference directly in the terminal:
llama cli -hf Josephgflowers/Tinyllama-Cinder-Agent-v1-GGUFUse pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Josephgflowers/Tinyllama-Cinder-Agent-v1-GGUF# Run inference directly in the terminal:
./llama-cli -hf Josephgflowers/Tinyllama-Cinder-Agent-v1-GGUFBuild from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Josephgflowers/Tinyllama-Cinder-Agent-v1-GGUF# Run inference directly in the terminal:
./build/bin/llama-cli -hf Josephgflowers/Tinyllama-Cinder-Agent-v1-GGUFUse Docker
docker model run hf.co/Josephgflowers/Tinyllama-Cinder-Agent-v1-GGUFThe 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 |
- Downloads last month
- 46
We're not able to determine the quantization variants.
Model tree for Josephgflowers/Tinyllama-Cinder-Agent-v1-GGUF
Base model
Josephgflowers/TinyLlama-3T-Cinder-v1.2
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf Josephgflowers/Tinyllama-Cinder-Agent-v1-GGUF# Run inference directly in the terminal: llama cli -hf Josephgflowers/Tinyllama-Cinder-Agent-v1-GGUF