Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use aisuko/ft-bert-base-uncased-for-binary-search with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aisuko/ft-bert-base-uncased-for-binary-search with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aisuko/ft-bert-base-uncased-for-binary-search")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aisuko/ft-bert-base-uncased-for-binary-search") model = AutoModelForSequenceClassification.from_pretrained("aisuko/ft-bert-base-uncased-for-binary-search", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96c997994e6e4404541ba6b0c137380a6a95e7a8f89e3c91dd6db8091ae6f14e
- Size of remote file:
- 5.24 kB
- SHA256:
- 3019045d8ca038d50d383ef7e0f0647a7e48b0889da2f3276f954da053279565
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