Text Classification
Transformers
Safetensors
English
distilbert
emotion
PyTorch
text-embeddings-inference
Instructions to use lucky377/emotion_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lucky377/emotion_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lucky377/emotion_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lucky377/emotion_classifier") model = AutoModelForSequenceClassification.from_pretrained("lucky377/emotion_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from lucky377/emotion_classifier: direct link, hf CLI and curl.
- Browser
- Download file 536 MB
-
https://huggingface.co/lucky377/emotion_classifier/resolve/main/optimizer.pt
- Command line
-
hf download hf://lucky377/emotion_classifier/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/lucky377/emotion_classifier/resolve/main/optimizer.pt
536 MB
- Xet hash:
- 96f4846a2178d51cbe252c9afaf6f6366b10784b555118dede5d1d0dd2027ead
- Size of remote file:
- 536 MB
- SHA256:
- 881a51c711fcfdeead2a33d420b7317e3cb01bab7f218c6dd71bbbf4e98c211b
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