Instructions to use Fabchi/Wayne_MLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fabchi/Wayne_MLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Fabchi/Wayne_MLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Fabchi/Wayne_MLM") model = AutoModelForMaskedLM.from_pretrained("Fabchi/Wayne_MLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5c45a00c58f68e21b5c85991b9ce52670bee9a60b1d84e4725133b937e27850
- Size of remote file:
- 329 MB
- SHA256:
- 1c57ac7f72996d36c4bdc52c6b33cc482515bb91d54ff54a11029913e9aa5110
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