Instructions to use zedalef/bert1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zedalef/bert1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zedalef/bert1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zedalef/bert1") model = AutoModelForSequenceClassification.from_pretrained("zedalef/bert1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b60c8f2e8bd3605cdaf8da14ac56d572d177b1e0c98fcc18cb4fa0bae6524669
- Size of remote file:
- 433 MB
- SHA256:
- 19d4e787b397a373fc8383d807027264d29af73c9d927633f3a8f860262cf050
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