Instructions to use Yannis98/tmp_natqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yannis98/tmp_natqa 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="Yannis98/tmp_natqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Yannis98/tmp_natqa") model = AutoModelForQuestionAnswering.from_pretrained("Yannis98/tmp_natqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Yannis98/tmp_natqa: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/Yannis98/tmp_natqa/resolve/main/training_args.bin
- Command line
-
hf download hf://Yannis98/tmp_natqa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Yannis98/tmp_natqa/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- a3583abcba811d9f60721c3ed974612e0203c1c357d78ffd47030644aea8e4f2
- Size of remote file:
- 5.43 kB
- SHA256:
- e47a168f129e10cfe08618468ba4f48e3e56aa71f3788cba2e7090e54277366e
路
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