Instructions to use llmware/slim-emotions-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use llmware/slim-emotions-onnx with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("llmware/slim-emotions-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d1a04a3149b286820bdb22fbcce3944b9f7f0e64fe3b474c49b3ae1f33a6645
- Size of remote file:
- 910 MB
- SHA256:
- 9ac3704c01502b8b0d9abf3ce6f2a7268a15bbd5a500dff797b9566c10ea942a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.