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:
- 340129d192dd8c07978b288d1395dec6e80c73f355293064869b398457b42e3d
- Size of remote file:
- 3.25 kB
- SHA256:
- d00a43357fdd89b9a49375fbfdc6b910ae0d60d489f0b8cc219a96d22655776d
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