Instructions to use diffuserconfuser/distilbert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diffuserconfuser/distilbert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="diffuserconfuser/distilbert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("diffuserconfuser/distilbert-base-uncased") model = AutoModelForQuestionAnswering.from_pretrained("diffuserconfuser/distilbert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c38c275b3ba344fe7dc62bb256d5cf65ac3e462040290c6bc8fcc3dd7668df2
- Size of remote file:
- 265 MB
- SHA256:
- ade19334c223339e45bb6635a4a90ded879b55a08163468dd280efeac73dcd0d
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.