Instructions to use ydshieh/tiny-random-LiltForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-LiltForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ydshieh/tiny-random-LiltForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-LiltForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("ydshieh/tiny-random-LiltForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d82b56784761a5dc5d132c7d7e18af2d7010823d76f8bfa7d37952dafabfef7
- Size of remote file:
- 296 kB
- SHA256:
- 378e47911910255580ae58be984db32a1769f3e79afe8684267107b02b77349a
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