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:
- 8983d1e30a03004810519a997246c2ee6db6a4d55ed8ceacb79cedf956c5683e
- Size of remote file:
- 134 MB
- SHA256:
- 593ca9cf1e8f95a553c18a8600b2a299339c9664b208535031f5dc01dddc487c
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