Instructions to use kwang2049/TSDAE-askubuntu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kwang2049/TSDAE-askubuntu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="kwang2049/TSDAE-askubuntu")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kwang2049/TSDAE-askubuntu") model = AutoModel.from_pretrained("kwang2049/TSDAE-askubuntu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4cd4d5c69c51f75442985ca1dbf3902c16aaff6f94767b7dffa678c9f14932b5
- Size of remote file:
- 438 MB
- SHA256:
- 945f2499c3c37dc87ed481820a70f0cf0e3e8f88d7fba494ceb718ba9fb5b65c
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