Instructions to use XRe03/my_awesome_qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use XRe03/my_awesome_qa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="XRe03/my_awesome_qa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("XRe03/my_awesome_qa_model") model = AutoModelForQuestionAnswering.from_pretrained("XRe03/my_awesome_qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 903df01081d6b25b5451dd7e965046a3237d05dd78973cd9bf5c7ebe4c8aae44
- Size of remote file:
- 5.2 kB
- SHA256:
- 72121cf49693f7576d8af077645bb5c43d2118874e84cd37d343ea71f3c0a3dd
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.