Instructions to use pouya-haghi/BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pouya-haghi/BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pouya-haghi/BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pouya-haghi/BERT") model = AutoModelForSequenceClassification.from_pretrained("pouya-haghi/BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1a7725edb25b245e25a7acca0d426e7fb37a360276018abe0f55732dded8640
- Size of remote file:
- 438 MB
- SHA256:
- b30b3d15d43a1366a5cde7ecf85bf51136a0b74759108014330a338f7b2cbfb2
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