Text Classification
Transformers
Safetensors
Laya
English
system-one
decision-model
android
mobile-agent
gui-agent
accessibility
androidcontrol
mmbert
Eval Results (legacy)
Instructions to use ByunByun/laya-android with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ByunByun/laya-android with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ByunByun/laya-android")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ByunByun/laya-android", device_map="auto") - Laya
How to use ByunByun/laya-android 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: 763 Bytes
98f7b69 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | {
"base_model": {
"repo": "convaiinnovations/laya",
"subfolder": "multilingual",
"revision": "7b928d828b7b0e022f929d9bd2e44165aa270148",
"laya_package": "0.3.28"
},
"max_len": 3072,
"head_max_len": 1536,
"training": {
"laya_android": {
"name": "laya-android-v0",
"base": "multilingual",
"train_steps": null,
"seed": 0,
"epochs": 3,
"micro_batch": 8,
"grad_accum": 4,
"encoder_lr": 2.5e-05,
"head_lr": 0.0001,
"loss": "soft-ce",
"shuffle_options": [
"choice"
],
"gradient_checkpointing": true
},
"best_epoch": 2,
"train_hours": 2.726,
"hardware": "NVIDIA GeForce RTX 4090"
},
"evaluations": [
"final_metrics.json",
"base_metrics.json",
"rtx4090.json"
]
} |