Instructions to use SchwallerGroup/CheMatE-v0-MLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SchwallerGroup/CheMatE-v0-MLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SchwallerGroup/CheMatE-v0-MLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SchwallerGroup/CheMatE-v0-MLM") model = AutoModelForMaskedLM.from_pretrained("SchwallerGroup/CheMatE-v0-MLM") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| library_name: transformers | |
| pipeline_tag: fill-mask | |
| language: | |
| - en | |
| tags: | |
| - fill-mask | |
| - chemistry | |
| - cheminformatics | |
| - modernbert | |
| # CheMatE (MLM base) | |
| The masked-language-modeling base for | |
| [`SchwallerGroup/CheMatE-v0`](https://huggingface.co/SchwallerGroup/CheMatE-v0): a ModernBERT | |
| model pretrained on SMILES-augmented chemistry text. For embeddings, use CheMatE-v0. | |
| ## Usage | |
| ```python | |
| from transformers import pipeline | |
| fill = pipeline("fill-mask", model="SchwallerGroup/CheMatE-v0-MLM") | |
| fill("Aspirin is a common [MASK].") | |
| ``` | |
| ## License | |
| MIT. | |