Instructions to use hung200504/bert-covidqa-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/bert-covidqa-5 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="hung200504/bert-covidqa-5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/bert-covidqa-5") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/bert-covidqa-5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from hung200504/bert-covidqa-5: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/hung200504/bert-covidqa-5/resolve/main/tokenizer.json
- Command line
-
hf download hf://hung200504/bert-covidqa-5/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/hung200504/bert-covidqa-5/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 485778097a33529a783fd130fe7a171457bb982a2b3e75a75db052b011b17eab
- Size of remote file:
- 16.3 MB
- SHA256:
- 338f230099c23cd536b4eb1823cfa31ea6108bf4fe506afbc3ee075b7e998dee
路
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