Instructions to use philschmid/distilbert-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/distilbert-onnx with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="philschmid/distilbert-onnx")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("philschmid/distilbert-onnx") model = AutoModelForQuestionAnswering.from_pretrained("philschmid/distilbert-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
model documentation
#2
by nazneen - opened
No description provided.
Hi @philschmid
This PR has documentation about your model and is based on the format we are using as part of our effort to standardize model cards at Hugging Face. Please feel free to merge as is or edit as you like and then merge.