Instructions to use ShynBui/s23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShynBui/s23 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="ShynBui/s23")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ShynBui/s23") model = AutoModelForQuestionAnswering.from_pretrained("ShynBui/s23", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ShynBui/s23: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/ShynBui/s23/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ShynBui/s23/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ShynBui/s23/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- b10e765b53eb61318af6319bb7d6fa13e15e9459e1b26d786e77da14204f1945
- Size of remote file:
- 431 MB
- SHA256:
- 51b7dd50270fe8cd445b9b72307447d68389c495c56651a54d39edf2353d3205
路
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