Instructions to use vashuag/HindiEmotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vashuag/HindiEmotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vashuag/HindiEmotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vashuag/HindiEmotion") model = AutoModelForSequenceClassification.from_pretrained("vashuag/HindiEmotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0be74d1413cac2faf9ef29664bb6fd2e3972c3b0d1836287a2c47b2b8872efcc
- Size of remote file:
- 15.3 MB
- SHA256:
- b1dde479dd4e493c0bea2cdefa97a961e84ba598a35311c44c4a8b1f56482220
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