Tiny Agent: FunctionGemma-270m-IT (Fine-Tuned)
This is a fine-tuned version of google/functiongemma-270m-it optimized for reliable function calling. It was trained as part of the "Tiny Agent Lab" project to distill the capabilities of larger models into a highly efficient 270M parameter model.
Model Description
- Model Type: Causal LM (Gemma)
- Language(s): English
- License: Gemma Terms of Use
- Finetuned from: google/functiongemma-270m-it
Capabilities
This model is designed to:
- Detect User Intent: Accurately identify when a tool call is needed.
- Generate Function Calls: Output valid
<start_function_call>XML/JSON blocks. - Refuse Out-of-Scope Requests: Politely decline requests for which no tool is available.
- Ask Clarification: Request missing parameter values interactively.
Performance (V4 Evaluation)
On a held-out test set of 100 diverse queries:
- Overall Accuracy: 71%
- Tool Selection Precision: 88%
- Tool Selection Recall: 94%
- F1 Score: 0.91
Usage
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "CuriousDragon/functiongemma-270m-tiny-agent"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype=torch.float16)
# ... (Add your inference code here)
Intended Use
This model is intended for research and educational purposes in building efficient agentic systems. It works best when provided with a clear system prompt defining the available tools.
- Downloads last month
- 15