Instructions to use ys7yoo/binary-inference_bert-base_lr5e-05_wd1e-03_bs8_ep10_plant_fold1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ys7yoo/binary-inference_bert-base_lr5e-05_wd1e-03_bs8_ep10_plant_fold1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ys7yoo/binary-inference_bert-base_lr5e-05_wd1e-03_bs8_ep10_plant_fold1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ys7yoo/binary-inference_bert-base_lr5e-05_wd1e-03_bs8_ep10_plant_fold1") model = AutoModelForSequenceClassification.from_pretrained("ys7yoo/binary-inference_bert-base_lr5e-05_wd1e-03_bs8_ep10_plant_fold1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d577eaa6294d36f765deb8c49ed9e1cde12fbb9c93409d38ed1a58b0e2b2e82
- Size of remote file:
- 443 MB
- SHA256:
- 553fce19ce2f6e8a2663ab29b5c1c4781c479497179d828900e87a2580136bdf
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