Text Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
Trained with AutoTrain
text-embeddings-inference
Instructions to use AyoubChLin/delberta_large_bbc_news with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AyoubChLin/delberta_large_bbc_news with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AyoubChLin/delberta_large_bbc_news")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AyoubChLin/delberta_large_bbc_news") model = AutoModelForSequenceClassification.from_pretrained("AyoubChLin/delberta_large_bbc_news", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87d1806ed445bf7f44849d5f49263469102259974b7567195c53c1136c6a4381
- Size of remote file:
- 1.74 GB
- SHA256:
- 53d1b95f4925e3b7b3847d215e6c0a13205ce28deda9e6dac718102d5751b13b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.