Instructions to use sucharush/MNLP_M2_document_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sucharush/MNLP_M2_document_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sucharush/MNLP_M2_document_encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sucharush/MNLP_M2_document_encoder") model = AutoModel.from_pretrained("sucharush/MNLP_M2_document_encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39de10494895cfb7b6cbdfb640152909d5f48964a6492b2c6cd52cd8f32348e1
- Size of remote file:
- 133 MB
- SHA256:
- 772487fa98b86cf51ec61e86b82e441b7ffe27b2a62179dae487bba07da68c76
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