Instructions to use asure22/dbert_qa_model_070623 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asure22/dbert_qa_model_070623 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="asure22/dbert_qa_model_070623")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("asure22/dbert_qa_model_070623") model = AutoModelForQuestionAnswering.from_pretrained("asure22/dbert_qa_model_070623", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from asure22/dbert_qa_model_070623: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/asure22/dbert_qa_model_070623/resolve/main/training_args.bin
- Command line
-
hf download hf://asure22/dbert_qa_model_070623/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/asure22/dbert_qa_model_070623/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- fff845d46e84451a9e795b6d4f8fd31a1d56a4a44b5989f08bc7139f6714253d
- Size of remote file:
- 3.9 kB
- SHA256:
- 3564486d5cf41f8443579b8b1bb0c28a7dcf455f047c72bb5fe41e0421be721e
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