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_") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 813e0543788a2395207bdccf06b33969e714b5c9a91d6fd5cc4c4f4292d23414
- Size of remote file:
- 440 MB
- SHA256:
- c63a1c72135c4a19ef47d446f9a2c078108d14f7a51152ca085300e3a8be3950
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