Instructions to use adith-ds/emotion-classifier-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adith-ds/emotion-classifier-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adith-ds/emotion-classifier-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adith-ds/emotion-classifier-v2") model = AutoModelForSequenceClassification.from_pretrained("adith-ds/emotion-classifier-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d57f23ab7b20f786f3ec511f266795c9c261747f5ac51158bca2d0258d1216fb
- Size of remote file:
- 5.78 kB
- SHA256:
- b9f8ea55d5fccab6b4ea950bec51e30efe1d0a414911af6c52593422e90ae309
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.