Instructions to use bowdpr/bowdpr_wiki with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bowdpr/bowdpr_wiki with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bowdpr/bowdpr_wiki")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bowdpr/bowdpr_wiki") model = AutoModelForMaskedLM.from_pretrained("bowdpr/bowdpr_wiki") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 024327b1130572a85389a21b321a33dc17e5f585a46665b4357fea62afb45aea
- Size of remote file:
- 438 MB
- SHA256:
- 468f9ba686f55434aca5907708c1e89f67d14d38b739aefa239657c2ae02019a
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