Instructions to use farid1088/qa_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use farid1088/qa_bert 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="farid1088/qa_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("farid1088/qa_bert") model = AutoModelForQuestionAnswering.from_pretrained("farid1088/qa_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from farid1088/qa_bert: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/farid1088/qa_bert/resolve/main/training_args.bin
- Command line
-
hf download hf://farid1088/qa_bert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/farid1088/qa_bert/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 658a2a6f9fdd777c836230729d40297b581ea117654dbb36e74920733dae97a0
- Size of remote file:
- 4.86 kB
- SHA256:
- f9a1f42433197c4d5ca04ee8720911ad1766a28b28c3e46801734705f6976236
路
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