Instructions to use aehrc/cxrmate-multi-tf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aehrc/cxrmate-multi-tf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="aehrc/cxrmate-multi-tf", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("aehrc/cxrmate-multi-tf", trust_remote_code=True) model = AutoModel.from_pretrained("aehrc/cxrmate-multi-tf", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fd3b63bfcd244f76518d6399a9e0efd70ee379bf9276a226c82c7c07dc2b2bb
- Size of remote file:
- 450 MB
- SHA256:
- 128c4fe34643bd3d0ee2648627dcb76a5c7cba2d602285b25fe3de06885d4867
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