Instructions to use corbinvking/rainmaker-roberta-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use corbinvking/rainmaker-roberta-qa with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="corbinvking/rainmaker-roberta-qa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("corbinvking/rainmaker-roberta-qa") model = AutoModelForQuestionAnswering.from_pretrained("corbinvking/rainmaker-roberta-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from corbinvking/rainmaker-roberta-qa: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/corbinvking/rainmaker-roberta-qa/resolve/main/training_args.bin
- Command line
-
hf download hf://corbinvking/rainmaker-roberta-qa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/corbinvking/rainmaker-roberta-qa/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 5bba48c3de5feb86ff9a79a39182235089c6001678f4334367b86e26beb2b079
- Size of remote file:
- 5.3 kB
- SHA256:
- 80484ad1828fb4cf395055b2d9e2e5d48fb549a953fa10aadd22501c914342b1
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