Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use Elron/deberta-v3-large-irony with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Elron/deberta-v3-large-irony with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Elron/deberta-v3-large-irony")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Elron/deberta-v3-large-irony") model = AutoModelForSequenceClassification.from_pretrained("Elron/deberta-v3-large-irony", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Elron/deberta-v3-large-irony: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/Elron/deberta-v3-large-irony/resolve/main/training_args.bin
- Command line
-
hf download hf://Elron/deberta-v3-large-irony/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Elron/deberta-v3-large-irony/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- c2891f4525ce54065bc762a571a918a85f8e33b1d8691cf170e6e0f4f4cfa6f8
- Size of remote file:
- 3.31 kB
- SHA256:
- a579f34da76ac1f097f1e3de8367214d02e4123e699bb75515a4919f6c59ae39
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.