Instructions to use xihajun/pruned_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xihajun/pruned_test 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="xihajun/pruned_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("xihajun/pruned_test") model = AutoModelForQuestionAnswering.from_pretrained("xihajun/pruned_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from xihajun/pruned_test: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/xihajun/pruned_test/resolve/main/training_args.bin
- Command line
-
hf download hf://xihajun/pruned_test/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/xihajun/pruned_test/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- 193744258eefc2585a01fb3ff0b46c662dc6322d8a6167f392844f6f0470bb25
- Size of remote file:
- 3.38 kB
- SHA256:
- 912141d1721cbef3604bcfe898867d216bab0e37c8050c02424cd780932e4214
路
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