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:
- 84dea5d36b2abe26404497d7571ceb9607821ae7f80332461f19b3bf01ddd747
- Size of remote file:
- 433 MB
- SHA256:
- 168b4a68724ec3f73f23e960258454f184e8d859edea5722d389679a6c088005
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