Text Classification
Transformers
TensorBoard
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use KobanBanan/table-continuation-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KobanBanan/table-continuation-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KobanBanan/table-continuation-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KobanBanan/table-continuation-classifier") model = AutoModelForSequenceClassification.from_pretrained("KobanBanan/table-continuation-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd58cb315532687ed6a87b90ec0771ed8e52429344dfc7f60e17aa211c38a3c1
- Size of remote file:
- 5.3 kB
- SHA256:
- 348911c9e9529afe9e6484e25bf6c699c1fdfa3a6c94f6cc9da49dfdde0a34d0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.