Instructions to use fatihasarmusakci/convbert_sentiment_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fatihasarmusakci/convbert_sentiment_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fatihasarmusakci/convbert_sentiment_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fatihasarmusakci/convbert_sentiment_model") model = AutoModelForSequenceClassification.from_pretrained("fatihasarmusakci/convbert_sentiment_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e33541c406f8099fa67a2888f41d8bd04a24114a83fe87aaa42f66065751deb5
- Size of remote file:
- 5.2 kB
- SHA256:
- 88facbdacf0feb63b74cf06d6697a032581b283c98b26b7525831c1aa0159926
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