Instructions to use arnabwithab/laya-android-control with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Laya
How to use arnabwithab/laya-android-control with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 1,220 Bytes
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license: apache-2.0
library_name: laya
base_model: convaiinnovations/laya
tags: [laya, system-one, android, phone-agent, decision-model]
---
# laya-android-control
Finetune of [convaiinnovations/laya](https://huggingface.co/convaiinnovations/laya) for **Android phone control**.
## Training data
- Source: [eros438/phone-decisions-ac](https://www.kaggle.com/datasets/eros438/phone-decisions-ac).
- That file holds 18,354 decision rows.
- The rows convert [xwm/AndroidControl](https://huggingface.co/datasets/xwm/AndroidControl).
- Training ran 4 epochs on a Kaggle T4 with `laya-train` defaults.
## Results
| Model | test operations accuracy |
|---|---|
| Base Laya-english | 0.261 |
| Head-only finetune | 0.574 |
| Full finetune | 0.665 |
In-sample calibration gave accuracy 0.85 and ECE 0.037.
## Use
```python
import laya
agent = laya.load("arnabwithab/laya-android-control", device="cuda")
agent.predict("Goal: ...", {"operation": {"type": "choice",
"instructions": "Which operation moves this phone task forward?",
"criteria": {"TAP": "...", "TYPE": "...", "SCROLL": "...",
"BACK": "...", "WAIT": "...", "DONE": "..."}}})
```
Serve it with `laya-serve` pointed at this repo.
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