Instructions to use Delicia/BiKirKinModelClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Delicia/BiKirKinModelClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Delicia/BiKirKinModelClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Delicia/BiKirKinModelClassification") model = AutoModelForSequenceClassification.from_pretrained("Delicia/BiKirKinModelClassification") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
288acf9 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:4d2fd4fdf6a027ee06c3da5bccd13b3754bb831a83ae863e142a4e4d6b3f35f7
size 2239667872
|