Instructions to use KienLe21/dpr_squadv2_finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KienLe21/dpr_squadv2_finetune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="KienLe21/dpr_squadv2_finetune")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("KienLe21/dpr_squadv2_finetune") model = AutoModel.from_pretrained("KienLe21/dpr_squadv2_finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from KienLe21/dpr_squadv2_finetune: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/KienLe21/dpr_squadv2_finetune/resolve/main/training_args.bin
- Command line
-
hf download hf://KienLe21/dpr_squadv2_finetune/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/KienLe21/dpr_squadv2_finetune/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 1d8475b25b522c5c45b4625a55fb43d4edb87c68a220c16ce225d5217c933d3a
- Size of remote file:
- 5.24 kB
- SHA256:
- 3fd21abc3e3672e43024e2db22911bef84cdb8cce8da1aa5d7502a94d16d43ef
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