Instructions to use aehrc/cxrmate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aehrc/cxrmate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="aehrc/cxrmate", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("aehrc/cxrmate", trust_remote_code=True) model = AutoModel.from_pretrained("aehrc/cxrmate", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7af9a70ad269f082e0dade067994429862f314ee44408787f8ab8c0ea5d6788
- Size of remote file:
- 450 MB
- SHA256:
- 2b6f5a6bef76e2e970e390b206919fd82c44b04ef6d7d4f7908c9e085192fbfb
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