Instructions to use Intel/bert-base-uncased-mnli-sparse-70-unstructured 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 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Intel/bert-base-uncased-mnli-sparse-70-unstructured")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Intel/bert-base-uncased-mnli-sparse-70-unstructured") model = AutoModelForSequenceClassification.from_pretrained("Intel/bert-base-uncased-mnli-sparse-70-unstructured") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd26fd7c0799b0cc05750b7b4db6c0fc96e9d33c79f4ff249ca6a9e392d7af41
- Size of remote file:
- 438 MB
- SHA256:
- a370285a8036e3e73a6d705bea65fb065d282614606abc88a2e3e2551a71388c
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