Instructions to use lakhera2023/tiny-bert-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lakhera2023/tiny-bert-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lakhera2023/tiny-bert-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lakhera2023/tiny-bert-classifier") model = AutoModelForSequenceClassification.from_pretrained("lakhera2023/tiny-bert-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bdfa07749035c55c5f4a4b925f71900eb9929723c576434787a1341db8950945
- Size of remote file:
- 17.5 MB
- SHA256:
- 09795617232724058918f0a2163db4f5ef3922d0c89b86fd611a5e4de8dd168e
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