Instructions to use DunnBC22/squeezebert-uncased-News_About_Gold with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/squeezebert-uncased-News_About_Gold with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DunnBC22/squeezebert-uncased-News_About_Gold")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DunnBC22/squeezebert-uncased-News_About_Gold") model = AutoModelForSequenceClassification.from_pretrained("DunnBC22/squeezebert-uncased-News_About_Gold") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44483ca958a7e8d59f49c941b7670c11f41891cf27bb3fbaa5f6c400fb63c948
- Size of remote file:
- 3.64 kB
- SHA256:
- abdf7f78d11b08d4f1313821ab6248e939304d55480ae35c806690a83fd7b32c
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