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:
- 4691355a710569b032bea2209f5a542d15e25f400ff3046bb1a3db0f706221b7
- Size of remote file:
- 3.38 kB
- SHA256:
- 6921bfaf11c78b53bfd3a3ca5bd3c20660231160829ae8ce61f4a0f168d774b9
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