Instructions to use swardiantara/drone-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use swardiantara/drone-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="swardiantara/drone-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("swardiantara/drone-sentiment") model = AutoModelForSequenceClassification.from_pretrained("swardiantara/drone-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a19cdef72cb1913d5f87e36c82e68f27a2749af6c3606b325515cb7a2baf4b4d
- Size of remote file:
- 329 MB
- SHA256:
- 4dd15c2491947ef6d5040b62fc0fe9136d57e92eda82d7f8b1964816226a8e31
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