Instructions to use ThuanPhong/ViReaderPlus_ViQuAD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThuanPhong/ViReaderPlus_ViQuAD 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="ThuanPhong/ViReaderPlus_ViQuAD")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ThuanPhong/ViReaderPlus_ViQuAD") model = AutoModelForQuestionAnswering.from_pretrained("ThuanPhong/ViReaderPlus_ViQuAD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ThuanPhong/ViReaderPlus_ViQuAD: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/ThuanPhong/ViReaderPlus_ViQuAD/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://ThuanPhong/ViReaderPlus_ViQuAD@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ThuanPhong/ViReaderPlus_ViQuAD/resolve/refs%2Fpr%2F1/tokenizer.json
17.1 MB
- Xet hash:
- 9fe433be5924bceeddc83249e594829fbd419be690aff4f243215b0d7423dc15
- Size of remote file:
- 17.1 MB
- SHA256:
- 87df8b5822e8de40a826123aac6fcd969f604772ff7754eb334529840f8501bc
路
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