Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use Elron/deberta-v3-large-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Elron/deberta-v3-large-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Elron/deberta-v3-large-emotion")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Elron/deberta-v3-large-emotion") model = AutoModelForSequenceClassification.from_pretrained("Elron/deberta-v3-large-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Elron/deberta-v3-large-emotion: direct link, hf CLI and curl.
- Browser
- Download file 1.74 GB
-
https://huggingface.co/Elron/deberta-v3-large-emotion/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Elron/deberta-v3-large-emotion/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Elron/deberta-v3-large-emotion/resolve/main/pytorch_model.bin
1.74 GB
- Xet hash:
- a0a3b30ae8e163f9887e4516f362c2f982ca97daad5fb977312447c9ab8f6f1a
- Size of remote file:
- 1.74 GB
- SHA256:
- e182efbb57bc6e4ecda054f4a41e886d02bcafcf1de64adf784d0e47c61f27ab
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