Instructions to use ArisuNguyen/processed_bart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArisuNguyen/processed_bart 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="ArisuNguyen/processed_bart")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ArisuNguyen/processed_bart") model = AutoModelForQuestionAnswering.from_pretrained("ArisuNguyen/processed_bart", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ArisuNguyen/processed_bart: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/ArisuNguyen/processed_bart/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ArisuNguyen/processed_bart/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ArisuNguyen/processed_bart/resolve/main/pytorch_model.bin
1.63 GB
- Xet hash:
- 6389628d087f79ad4ca24ca18d1a618d64539e6741b82448b397abff01925aa3
- Size of remote file:
- 1.63 GB
- SHA256:
- 80d2a5f355c4513cca4bfde351b6ad0a51e7fe6178ae94024d650f74a05b6eab
路
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