Text Classification
Transformers
PyTorch
TensorBoard
deberta
Generated from Trainer
Eval Results (legacy)
Instructions to use Tomor0720/deberta-large-finetuned-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tomor0720/deberta-large-finetuned-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tomor0720/deberta-large-finetuned-sst2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tomor0720/deberta-large-finetuned-sst2") model = AutoModelForSequenceClassification.from_pretrained("Tomor0720/deberta-large-finetuned-sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Tomor0720/deberta-large-finetuned-sst2: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/Tomor0720/deberta-large-finetuned-sst2/resolve/main/training_args.bin
- Command line
-
hf download hf://Tomor0720/deberta-large-finetuned-sst2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Tomor0720/deberta-large-finetuned-sst2/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- ba1b65e7433029b5fd552a665026feae73f3c3e1016e838f1a59d2949620c68d
- Size of remote file:
- 3.45 kB
- SHA256:
- 4549e7eb1d20bb870bfd4525a01126152824cef853b2097844f568105fc8bf80
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