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 training_args.bin from lucky377/emotion_classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/lucky377/emotion_classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://lucky377/emotion_classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lucky377/emotion_classifier/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- e23e512eed760228c0c3b8e880426241327f3dc1c362dad578a41974a0ce1763
- Size of remote file:
- 5.2 kB
- SHA256:
- 94c7c854dfca235d342cca41e9e578b2a34f0553b99e055c06044e0a9aa78e22
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