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
Upload README.md with huggingface_hub
Browse files
README.md
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# Fast Emotion-X: Fine-tuned DeBERTa V3 Small Based Emotion Detection
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This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) for emotion detection using the [dair-ai/emotion](https://huggingface.co/dair-ai/emotion) dataset.
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# Fast Emotion-X: Fine-tuned DeBERTa V3 Small Based Emotion Detection
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This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) for emotion detection using the [dair-ai/emotion](https://huggingface.co/dair-ai/emotion) dataset.
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