Instructions to use philschmid/distilbert-neuron with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/distilbert-neuron with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="philschmid/distilbert-neuron")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("philschmid/distilbert-neuron") model = AutoModelForQuestionAnswering.from_pretrained("philschmid/distilbert-neuron", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b16d33ad14ba66b6f5f8dd4626094e4207a159290ceef5c8e47d75220234cc33
- Size of remote file:
- 160 MB
- SHA256:
- 56d7063e6a79afb0fe17d83ba48360934eb36c3b7aed0b36b4e69b5ee9a5c9f3
路
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