Instructions to use lkk688/eli5asksciencemodeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lkk688/eli5asksciencemodeling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lkk688/eli5asksciencemodeling")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lkk688/eli5asksciencemodeling") model = AutoModelForMaskedLM.from_pretrained("lkk688/eli5asksciencemodeling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lkk688/eli5asksciencemodeling: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/lkk688/eli5asksciencemodeling/resolve/2acd3065a23c4a6cd2d7decc75ca46e4a41da2ef/training_args.bin
- Command line
-
hf download hf://lkk688/eli5asksciencemodeling@2acd3065a23c4a6cd2d7decc75ca46e4a41da2ef/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lkk688/eli5asksciencemodeling/resolve/2acd3065a23c4a6cd2d7decc75ca46e4a41da2ef/training_args.bin
4.03 kB
- Xet hash:
- 0f612cbb58545ba4f8010d84230fe50d28bf92fcdfdeff5fa22e04b43b087fed
- Size of remote file:
- 4.03 kB
- SHA256:
- 71f59b5ceb7101bf0208b955adbb7e51dd3a7f1ade00f9e08dee13d2a47964f7
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