Instructions to use sofom/roberta-base-m4_extended with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sofom/roberta-base-m4_extended with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sofom/roberta-base-m4_extended")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sofom/roberta-base-m4_extended") model = AutoModel.from_pretrained("sofom/roberta-base-m4_extended") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27426504defb71fcdb3a422ebba14ace6ac286ce98ce1f87d06a044009c94b88
- Size of remote file:
- 249 MB
- SHA256:
- a005744817e989dc39f15f47a2bd00ea6a2550f44947f9f86266b56bc09b42b2
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