Text Classification
Transformers
ONNX
Laya
TensorRT
multilingual
jev-compatible
system-one
decision-model
typed-decisions
non-autoregressive
mmbert
rknn
rockchip
rk3588
jetson
edge
int8
calibrated-decisions
Instructions to use harvestsu/laya-multilingual-rknn-tensorrt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harvestsu/laya-multilingual-rknn-tensorrt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harvestsu/laya-multilingual-rknn-tensorrt")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("harvestsu/laya-multilingual-rknn-tensorrt", device_map="auto") - Laya
How to use harvestsu/laya-multilingual-rknn-tensorrt 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
- TensorRT
How to use harvestsu/laya-multilingual-rknn-tensorrt with TensorRT:
# 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
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