Instructions to use ugurcanvurgun/DistilBERT_SST2_ASD_SentimentAnalysis_withAugmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ugurcanvurgun/DistilBERT_SST2_ASD_SentimentAnalysis_withAugmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ugurcanvurgun/DistilBERT_SST2_ASD_SentimentAnalysis_withAugmentation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ugurcanvurgun/DistilBERT_SST2_ASD_SentimentAnalysis_withAugmentation") model = AutoModelForSequenceClassification.from_pretrained("ugurcanvurgun/DistilBERT_SST2_ASD_SentimentAnalysis_withAugmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a537c9df451dcffbf90f313b1b460f862b9ccc89da3833d16830843c5b22902
- Size of remote file:
- 268 MB
- SHA256:
- 2037a6f9c1ae40008bfef763e56bc25eccfbbff750f739a57518693ca5727eb4
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