Instructions to use badokorach/qa_afroxml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use badokorach/qa_afroxml 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="badokorach/qa_afroxml")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("badokorach/qa_afroxml") model = AutoModelForQuestionAnswering.from_pretrained("badokorach/qa_afroxml", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from badokorach/qa_afroxml: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/badokorach/qa_afroxml/resolve/main/training_args.bin
- Command line
-
hf download hf://badokorach/qa_afroxml/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/badokorach/qa_afroxml/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- f59decdbfbca9c7075fa1c24cee5859570b9d78cd5a21c613ac90e4837b6e72c
- Size of remote file:
- 3.58 kB
- SHA256:
- b5de7dd247fb3bcbc0c2dced2cc0311793bc3ab6864d37bf590ede454f10d5fe
路
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