Instructions to use andyluan/emotion-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andyluan/emotion-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="andyluan/emotion-detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("andyluan/emotion-detection") model = AutoModelForSequenceClassification.from_pretrained("andyluan/emotion-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from andyluan/emotion-detection: direct link, hf CLI and curl.
- Browser
- Download file 14.5 MB
-
https://huggingface.co/andyluan/emotion-detection/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://andyluan/emotion-detection@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/andyluan/emotion-detection/resolve/refs%2Fpr%2F1/tokenizer.json
14.5 MB
- Xet hash:
- 6c21e9666e897e46d97ee9f1fe6ad56639936c0ff441d032978a49bb0e0fd08a
- Size of remote file:
- 14.5 MB
- SHA256:
- 17a208233d2ee8d8c83b23bc214df737c44806a1919f444e89b31e586cd956ba
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