Text Classification
Transformers
PyTorch
Safetensors
English
custom_multilabel_emotion
emotion-classification
multilabel-classification
Instructions to use EnJiZ/FirstTimeUp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EnJiZ/FirstTimeUp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EnJiZ/FirstTimeUp")# pip install -U transformers accelerate # Load model directly from transformers import MultiLabelEmotionClassifier model = MultiLabelEmotionClassifier.from_pretrained("EnJiZ/FirstTimeUp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from EnJiZ/FirstTimeUp: direct link, hf CLI and curl.
- Browser
- Download file 266 MB
-
https://huggingface.co/EnJiZ/FirstTimeUp/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://EnJiZ/FirstTimeUp/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/EnJiZ/FirstTimeUp/resolve/main/pytorch_model.bin
266 MB
- Xet hash:
- 1a37e9e112f6f1c8f621ed427b447f6535adc4e1519849598ea0971eddfe5291
- Size of remote file:
- 266 MB
- SHA256:
- 6d68b6f0217225e55b1a08e8d458499abd02a16a2ffeb12ba90269e41c78c126
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