Instructions to use yigitkucuk/Sentimentale with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yigitkucuk/Sentimentale with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yigitkucuk/Sentimentale")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yigitkucuk/Sentimentale") model = AutoModelForSequenceClassification.from_pretrained("yigitkucuk/Sentimentale", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c18d4dc3da47c00c0dadef7e42c5fc3dc88ebfa3c4193267689d9f4f9e896029
- Size of remote file:
- 433 MB
- SHA256:
- a1e8ff3c2822e9390986b0cc8aae3f2f546c273a20a13ff8c81207dea5255e77
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