Text Classification
Transformers
Safetensors
English
deberta-v2
feature-extraction
ielts
automated-essay-scoring
deberta-v3
regression
nlp
custom_code
text-embeddings-inference
Instructions to use star092304/ielts-writing-task2-debertav3base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use star092304/ielts-writing-task2-debertav3base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="star092304/ielts-writing-task2-debertav3base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("star092304/ielts-writing-task2-debertav3base", trust_remote_code=True) model = AutoModel.from_pretrained("star092304/ielts-writing-task2-debertav3base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_curves.png from star092304/ielts-writing-task2-debertav3base: direct link, hf CLI and curl.
- Browser
- Download file 527 kB
-
https://huggingface.co/star092304/ielts-writing-task2-debertav3base/resolve/main/training_curves.png
- Command line
-
hf download hf://star092304/ielts-writing-task2-debertav3base/training_curves.png
-
curl -L -o training_curves.png https://huggingface.co/star092304/ielts-writing-task2-debertav3base/resolve/main/training_curves.png
527 kB

- Xet hash:
- 7531dd6f08a85a2e3309ec5652f04e8381eb2f455d0020ffbaa5c625ea723f41
- Size of remote file:
- 527 kB
- SHA256:
- c90b97d53c6337c741416408a898ce9ea136eb6cae49a649230227b883f23083
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.