Instructions to use Intel/bert-base-uncased-mnli-sparse-70-unstructured-no-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/bert-base-uncased-mnli-sparse-70-unstructured-no-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Intel/bert-base-uncased-mnli-sparse-70-unstructured-no-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Intel/bert-base-uncased-mnli-sparse-70-unstructured-no-classifier") model = AutoModelForMaskedLM.from_pretrained("Intel/bert-base-uncased-mnli-sparse-70-unstructured-no-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56d8213e72e53f24a950f39dac058883c6bf64d7eff2eefa976828dce81ce3a1
- Size of remote file:
- 438 MB
- SHA256:
- 955735e9502bbbb96f358a3db7af654d4cd272cb0fa5390f39369ee060d8084d
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