Instructions to use dedebo/qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dedebo/qa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="dedebo/qa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("dedebo/qa_model") model = AutoModelForQuestionAnswering.from_pretrained("dedebo/qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67f82b3408534d360dfe240923a0c5780391dcfc33703fc16e5df01242875c60
- Size of remote file:
- 4.66 kB
- SHA256:
- 20349190bc177fcc5836241848b0abd1ef6c3633bf789cc5b052e240ed5f1cc6
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.