Instructions to use DSI/human-directed-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DSI/human-directed-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DSI/human-directed-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DSI/human-directed-sentiment") model = AutoModelForSequenceClassification.from_pretrained("DSI/human-directed-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 785f4db59bb3f4ef0a8eb3f03234217f459bc054aa41b482e2570a3f10ba765d
- Size of remote file:
- 651 MB
- SHA256:
- b5bcb80989e85e774f9cef1eda514a53cef65dae9b9f0e92cb307d5dffa92839
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