Instructions to use JuliusAlphonso/distilbert-plutchik with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JuliusAlphonso/distilbert-plutchik with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JuliusAlphonso/distilbert-plutchik")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JuliusAlphonso/distilbert-plutchik") model = AutoModelForSequenceClassification.from_pretrained("JuliusAlphonso/distilbert-plutchik", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e5131faf22b687dba58fcb4f05b3cd49198c0f74ae4d19818d954d3ebf94877
- Size of remote file:
- 263 MB
- SHA256:
- f7f8a791dc9a715bfff1cbfc731aa4044e1e5526d208cb791417818eae4dfb28
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