Instructions to use taesu/ts-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use taesu/ts-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="taesu/ts-test")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("taesu/ts-test") model = AutoModelForMaskedLM.from_pretrained("taesu/ts-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4e9c6683518abc9c734a59eb0ceb8680111e4fe34db331145b9a758159a5b2f
- Size of remote file:
- 438 MB
- SHA256:
- 00356d95e5557a5d6dc663ddb3a4ba07b17dae82e745fb04f0785d10b8b50fcb
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