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")# pip install -U transformers accelerate # 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
Commit History
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upload flax model
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allow flax
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Update tokenizer_config.json
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Update vocab.txt
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Update tf_model.h5
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Update pytorch_model.bin
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Update special_tokens_map.json
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Update config.json
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initial commit
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