Instructions to use Sayan01/tiny-bert-sst2-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sayan01/tiny-bert-sst2-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sayan01/tiny-bert-sst2-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sayan01/tiny-bert-sst2-distilled") model = AutoModelForSequenceClassification.from_pretrained("Sayan01/tiny-bert-sst2-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7fcb37361b31be7a0388db6169f9ccd8e4535cbd7fa6991973ae92ae4f59c55
- Size of remote file:
- 57.4 MB
- SHA256:
- cbfc131ed5ef86d4474cad6d70f2116f06033eec4b054d463990743684923fa3
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