Instructions to use M-Chimiste/MiniLM-L-12-StackOverflow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M-Chimiste/MiniLM-L-12-StackOverflow with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="M-Chimiste/MiniLM-L-12-StackOverflow")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("M-Chimiste/MiniLM-L-12-StackOverflow") model = AutoModelForMaskedLM.from_pretrained("M-Chimiste/MiniLM-L-12-StackOverflow", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44fcaa8693f5a91add75911b2879c6f42909aafabee6e895cfc4766954a04317
- Size of remote file:
- 134 MB
- SHA256:
- 3bf0e6748d6e7832d6df8217dd3a696f333865ac28fa3b222e9566f3ea7e9f27
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