Instructions to use oberbics/test_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oberbics/test_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="oberbics/test_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("oberbics/test_bert") model = AutoModelForSequenceClassification.from_pretrained("oberbics/test_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8007c5d67a8a1b6183711134a48d570d7a4a73a51d1ff01e2874af14d98c3bba
- Size of remote file:
- 268 MB
- SHA256:
- c7560cb7ba741197a730fab525cb0bd3e1e25b8a2b4eacffe7f84276172dda6b
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