Instructions to use adalbertojunior/mrpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adalbertojunior/mrpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="adalbertojunior/mrpt", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("adalbertojunior/mrpt", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("adalbertojunior/mrpt", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52c9bac0b3b8712c0c346ddd017832a66c0bfd2f1db2cb723f113954ddc350b9
- Size of remote file:
- 499 MB
- SHA256:
- 2bb13c90b4ac4fea8fb5d5423b01228be0aa34d64cba7737952d069c9439de0d
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