Text Classification
Transformers
PyTorch
English
roberta
distilroberta
sentiment
emotion
twitter
reddit
text-embeddings-inference
Instructions to use michelleli99/emotion_text_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michelleli99/emotion_text_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="michelleli99/emotion_text_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("michelleli99/emotion_text_classifier") model = AutoModelForSequenceClassification.from_pretrained("michelleli99/emotion_text_classifier", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from michelleli99/emotion_text_classifier: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/michelleli99/emotion_text_classifier/resolve/refs%2Fpr%2F13/pytorch_model.bin
- Command line
-
hf download hf://michelleli99/emotion_text_classifier@refs/pr/13/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/michelleli99/emotion_text_classifier/resolve/refs%2Fpr%2F13/pytorch_model.bin
329 MB
- Xet hash:
- e4014e7689b7b2c4099c78a6bd94e2872f3e8a5801ea6fde4eaac8680880ca04
- Size of remote file:
- 329 MB
- SHA256:
- 0b2d2aa01be2780dc2b565510e4f525f8963f4957d3e7f702f964f1df1cbe916
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