Instructions to use WhoCares258/my_awesome_qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WhoCares258/my_awesome_qa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="WhoCares258/my_awesome_qa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("WhoCares258/my_awesome_qa_model") model = AutoModelForQuestionAnswering.from_pretrained("WhoCares258/my_awesome_qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from WhoCares258/my_awesome_qa_model: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/WhoCares258/my_awesome_qa_model/resolve/main/training_args.bin
- Command line
-
hf download hf://WhoCares258/my_awesome_qa_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/WhoCares258/my_awesome_qa_model/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 78390ca4b5bbaab01975797c56774246c510b42fda8f31d393467f8ff3d106e3
- Size of remote file:
- 5.3 kB
- SHA256:
- 86172fb3122eb1dae6194b999fb5de2fc6edd6ac885ecc2fb60846c84dc26648
路
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