metadata
license: apache-2.0
base_model: google/functiongemma-270m-it
tags:
- gemma
- function-calling
- tool-use
- gguf
- ollama
model-index:
- name: delia-functiongemma-270m-gguf
results: []
Delia FunctionGemma 270M - GGUF
This is the GGUF version of delia-functiongemma-270m, fine-tuned for Delia MCP tool orchestration.
Quick Start with Ollama
# Download the GGUF file
wget https://huggingface.co/devopsforflops/delia-functiongemma-270m-gguf/resolve/main/functiongemma-delia-f16.gguf
# Create Modelfile
cat > Modelfile << 'MODELFILE'
FROM ./functiongemma-delia-f16.gguf
TEMPLATE """{{ if .System }}<start_of_turn>developer
{{ .System }}
<end_of_turn>
{{ end }}<start_of_turn>user
{{ .Prompt }}
<end_of_turn>
<start_of_turn>model
"""
PARAMETER stop <end_of_turn>
PARAMETER stop <start_of_turn>
PARAMETER temperature 0.1
PARAMETER num_ctx 2048
MODELFILE
# Import to Ollama
ollama create functiongemma-delia -f Modelfile
# Test it
ollama run functiongemma-delia "Hello!"
Model Details
| Property | Value |
|---|---|
| Base Model | google/functiongemma-270m-it |
| Architecture | Gemma3 |
| Parameters | 268M |
| Quantization | F16 (full precision) |
| File Size | ~518 MB |
| Context Length | 2048 tokens |
Training
Fine-tuned using LoRA on Delia MCP tool calling examples:
- LoRA rank: 16
- LoRA alpha: 64
- Epochs: 20
- Dataset: 27 training examples from Delia test suite
Use with Delia
Add to your Delia settings.json:
{
"model_dispatcher": {
"name": "functiongemma-delia",
"num_ctx": 2048
}
}
Important: The model name must contain "functiongemma" for Delia to apply the correct prompt formatting.
Related Models
- delia-functiongemma-270m - Full merged HuggingFace model
- delia-functiongemma-270m-lora - LoRA adapter only
License
Apache 2.0