Instructions to use eki1381/practice-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eki1381/practice-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eki1381/practice-sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eki1381/practice-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("eki1381/practice-sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39c098707353a174836ee4674af8319beb6a00e48cc8eae7270c4494e552e259
- Size of remote file:
- 268 MB
- SHA256:
- 4bb8fc87d916d754c1af07381162537d54a21eb7114496d247c7e5943932343e
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