README.md

---
language:
- en
- fr
license: apache-2.0
base_model: unsloth/functiongemma-270m-it
library_name: gguf
pipeline_tag: text-generation
tags:
- gguf
- llama.cpp
- function-calling
- tool-calling
- gemma
- bilingual
- en
- fr
- finetuned
model_name: function-gemma-finetuned-tool-call
---

# function-gemma-finetuned-tool-call

Fine-tuned Function-Gemma 270M model for bilingual (English/French) tool-calling.

## Files

- `function-gemma-finetuned-tool-call.gguf` (F16 merged GGUF)

## Base Model

- `unsloth/functiongemma-270m-it`

## Training Summary

- Method: SFT + LoRA, then merged into full weights
- Dataset: custom bilingual EN/FR tool-calling set (`dataset_80tools_en_fr.json`)
- Target behavior: structured function/tool calls with argument extraction and no-tool abstention when appropriate

## Local Evaluation (checkpoint benchmark)

From `outputs/eval_checkpoint_report.json`:

- Total cases: 16
- Pass rate: 0.8125
- Decision accuracy: 0.8125
- Tool name accuracy: 0.8125
- Argument presence accuracy: 1.0
- Tool-call recall: 1.0
- No-tool precision: 0.5

## Usage (llama.cpp)

```bash
llama.cpp/build/bin/llama-cli \
  --model function-gemma-finetuned-tool-call.gguf \
  --ctx-size 32768 \
  --n-gpu-layers 99 \
  --seed 3407 \
  --top-k 64 \
  --top-p 0.95 \
  --temp 1.0 \
  --jinja
```

For one-shot test:

```bash
llama.cpp/build/bin/llama-cli \
  --model function-gemma-finetuned-tool-call.gguf \
  --ctx-size 32768 \
  --n-gpu-layers 99 \
  --seed 3407 \
  --top-k 64 \
  --top-p 0.95 \
  --temp 1.0 \
  --jinja \
  --single-turn \
  --simple-io \
  --prompt "What is the weather in Paris?"
```

## Prompt / Output Format

This model was fine-tuned for Function-Gemma style tool tags (e.g. `<start_function_call>...`).
When used with `--jinja`, llama.cpp applies the chat template stored in GGUF metadata.

## Limitations

- Small model (270M): can still over-call tools in ambiguous no-tool prompts.
- Best results require strong tool schema prompts and clear user intent.

## Intended Use

- Lightweight local assistant prototypes
- Tool-routing and structured argument extraction tasks
- EN/FR bilingual demos and experimentation