Text Classification
Transformers
English
multilingual
laya
typed-decisions
non-autoregressive
axera
ax650
Instructions to use AXERA-TECH/Laya with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AXERA-TECH/Laya with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AXERA-TECH/Laya")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AXERA-TECH/Laya", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| # Python inference | |
| The two Python runtimes are isolated because they target different hardware and dependencies. | |
| | Directory | Backend | Model files | | |
| | --- | --- | --- | | |
| | `ax650/` | PyAXEngine on AX650 / NPU3 | Packaged `*.axmodel` files | | |
| | `pytorch/` | PyTorch on CPU, CUDA, or MPS | Original upstream FP checkpoints | | |
| See the repository root `README.md` for installation and run commands. | |