Instructions to use farid1088/qa_bert_training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use farid1088/qa_bert_training 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_training")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("farid1088/qa_bert_training") model = AutoModelForQuestionAnswering.from_pretrained("farid1088/qa_bert_training", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from farid1088/qa_bert_training: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/farid1088/qa_bert_training/resolve/main/training_args.bin
- Command line
-
hf download hf://farid1088/qa_bert_training/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/farid1088/qa_bert_training/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- b1237694554e33875d99214d1907404b30c60bd0a4cda742adf834adda585739
- Size of remote file:
- 4.73 kB
- SHA256:
- 104d6f7d9c1d0cd06e380ab16159fe6ca75b9223b25666c98f10385c5add4c02
路
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