Instructions to use n0w0f/MatText-atom-seq-plusplus-2m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use n0w0f/MatText-atom-seq-plusplus-2m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="n0w0f/MatText-atom-seq-plusplus-2m")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("n0w0f/MatText-atom-seq-plusplus-2m") model = AutoModel.from_pretrained("n0w0f/MatText-atom-seq-plusplus-2m") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6419bbda563072bffc24caa5b5de38a4b1a9337c8f6333af2ef9a9e92c9816dc
- Size of remote file:
- 131 MB
- SHA256:
- c52225e99d4cae630c70fc656e778fb69e061dcd89792064386f58c5dab61d60
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