Instructions to use JanSt/gbert-base-finetuned-twitter_ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JanSt/gbert-base-finetuned-twitter_ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="JanSt/gbert-base-finetuned-twitter_")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("JanSt/gbert-base-finetuned-twitter_") model = AutoModelForMaskedLM.from_pretrained("JanSt/gbert-base-finetuned-twitter_", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 561d55101b16986ffcf77463975d857a4ec6888611ef5cb1135ccc8311631453
- Size of remote file:
- 4.03 kB
- SHA256:
- 61e3874e4ce501897840516e49bfaef5d0c3d92a2c97bccda3d7c52365dddb00
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