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
- Xet hash:
- 117c4a2e305cc971a5bd5504d93d5f338f2750b1f0281095d65c07d470b0507f
- Size of remote file:
- 568 MB
- SHA256:
- 868824e6c931200b3e72e6dd6ba040fcbd46a73def5d2f08ca8be0ae8e3d4de5
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