Instructions to use lisdarr/19_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lisdarr/19_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lisdarr/19_model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lisdarr/19_model") model = AutoModelForMaskedLM.from_pretrained("lisdarr/19_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2476e3abf0fb5364f444ddc714864e3865e95d9a4dff565204ef467f8411bda1
- Size of remote file:
- 412 MB
- SHA256:
- 68d854f9722218a07a24feffc19ccf37c5fc6aa7aa65aa9be020fb6c1b7e1236
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