Instructions to use taesu/ts-test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use taesu/ts-test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="taesu/ts-test2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("taesu/ts-test2") model = AutoModelForMaskedLM.from_pretrained("taesu/ts-test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76ef44fabc6d8c7c0011b8f5c9fbb18ede88114f8b1cda72987a320ae2096733
- Size of remote file:
- 438 MB
- SHA256:
- d1cf63cbd81b02d4378eeba944f3ee6d282a0de3cb0d79ed9b4895a674205b83
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