Instructions to use n0w0f/MatText-cifsymmetrized-2m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use n0w0f/MatText-cifsymmetrized-2m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="n0w0f/MatText-cifsymmetrized-2m")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("n0w0f/MatText-cifsymmetrized-2m") model = AutoModel.from_pretrained("n0w0f/MatText-cifsymmetrized-2m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 111fe2cee62996be6999bfa2a39f8d8a0b22ff5b723ed2fd813636b6cf4f92a1
- Size of remote file:
- 133 MB
- SHA256:
- d0de5a1e068d07d6d701bb677f32ec1e9b4b14d978dafd3f3a98be175a5c3a61
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