Text Classification
Transformers
Safetensors
English
deberta-v2
debarta
debarta-v3-small
emotions-classifier
text-embeddings-inference
Instructions to use AnkitAI/deberta-v3-small-base-emotions-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnkitAI/deberta-v3-small-base-emotions-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnkitAI/deberta-v3-small-base-emotions-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnkitAI/deberta-v3-small-base-emotions-classifier") model = AutoModelForSequenceClassification.from_pretrained("AnkitAI/deberta-v3-small-base-emotions-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download banner.svg from AnkitAI/deberta-v3-small-base-emotions-classifier: direct link, hf CLI and curl.
- Browser
- Download file 237 kB
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https://huggingface.co/AnkitAI/deberta-v3-small-base-emotions-classifier/resolve/7591d02fba37483ee4ee62f7fe86a0ec871bf3a2/banner.svg
- Command line
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hf download hf://AnkitAI/deberta-v3-small-base-emotions-classifier@7591d02fba37483ee4ee62f7fe86a0ec871bf3a2/banner.svg
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curl -L -o banner.svg https://huggingface.co/AnkitAI/deberta-v3-small-base-emotions-classifier/resolve/7591d02fba37483ee4ee62f7fe86a0ec871bf3a2/banner.svg
237 kB