Instructions to use Camilla9000/imdb-sentiment-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Camilla9000/imdb-sentiment-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Camilla9000/imdb-sentiment-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Camilla9000/imdb-sentiment-classifier") model = AutoModelForSequenceClassification.from_pretrained("Camilla9000/imdb-sentiment-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe3aeba54352928fca0b4c89861a1f3d6db655596c2c35d618341efc2cccd67a
- Size of remote file:
- 268 MB
- SHA256:
- 823355576b01db9f0889bf04c94c6c7ce76f13126c0c5f94a45d26051e1d24a6
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