Instructions to use nanom/vizwiz-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nanom/vizwiz-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nanom/vizwiz-bert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nanom/vizwiz-bert-base") model = AutoModelForMaskedLM.from_pretrained("nanom/vizwiz-bert-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59f133086f3eb77414e67d3b95956bd4f3b6ccf170c41d2636e7f306efe59349
- Size of remote file:
- 438 MB
- SHA256:
- c3486a152996f4c8e5c723ee2fc8e26843e47ee9b92d2f54ba1bdf11535ebe36
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