Instructions to use poom-sci/distilbert-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use poom-sci/distilbert-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="poom-sci/distilbert-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("poom-sci/distilbert-qa") model = AutoModelForQuestionAnswering.from_pretrained("poom-sci/distilbert-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74efdff1d1982a20384d135bfdee21c1eba4bcb900d0094255222b73bee72532
- Size of remote file:
- 265 MB
- SHA256:
- f0034ee3df7f89757a2cb59aa1c7cd6da8ca9f99605218d804cc9e8ec9ccdcdc
路
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