Instructions to use ENLP/mrasp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ENLP/mrasp with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="ENLP/mrasp", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ENLP/mrasp", trust_remote_code=True) model = AutoModel.from_pretrained("ENLP/mrasp", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec1cfd1a819ccc01199d8e5b748e0fa71e55f6c9888948321e466b7722f909a7
- Size of remote file:
- 974 MB
- SHA256:
- 63d8c31787dc3bd02602e3490a447a9e4b8dd902bb7053b5970a55e2ac9b55af
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