Instructions to use rohitLearning/emotionModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rohitLearning/emotionModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rohitLearning/emotionModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rohitLearning/emotionModel") model = AutoModelForSequenceClassification.from_pretrained("rohitLearning/emotionModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from rohitLearning/emotionModel: direct link, hf CLI and curl.
- Browser
- Download file 8 Bytes
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https://huggingface.co/rohitLearning/emotionModel/resolve/main/README.md
- Command line
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hf download hf://rohitLearning/emotionModel/README.md
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curl -L -H "Authorization: Bearer $HF_TOKEN" -o README.md https://huggingface.co/rohitLearning/emotionModel/resolve/main/README.md
8 Bytes
Learning