Instructions to use sshleifer/tiny-distilbert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/tiny-distilbert-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sshleifer/tiny-distilbert-base-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sshleifer/tiny-distilbert-base-cased") model = AutoModelForTokenClassification.from_pretrained("sshleifer/tiny-distilbert-base-cased", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13db6a225c6f5add57b8f3b26374c5a34adba48a79c0a5b529c4878080c3ec59
- Size of remote file:
- 246 kB
- SHA256:
- fa18ca3cf53c2c5f742d17023ad88941107ec151ff2bca567b87fcbd70f21308
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