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
File size: 397 Bytes
5acccb6 | 1 2 3 4 5 6 7 8 9 10 11 | # 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.
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