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:
- 9613c9f34e0df0532b2c40dae3e6664f6df66ee6232097581a392677f4ba51f7
- Size of remote file:
- 876 MB
- SHA256:
- 124ca5cb2fcd05c5f31c35fc6a3e335113b7493bbac73fa19c6bac4973666c1e
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