Instructions to use Labib11/pmc-uae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Labib11/pmc-uae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Labib11/pmc-uae")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Labib11/pmc-uae") model = AutoModel.from_pretrained("Labib11/pmc-uae", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Labib11/pmc-uae: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/Labib11/pmc-uae/resolve/main/training_args.bin
- Command line
-
hf download hf://Labib11/pmc-uae/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Labib11/pmc-uae/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- cd1ea3c82e4bf827a2abe00bc495535ebc86448793bfec04ce3ef7110979658f
- Size of remote file:
- 5.05 kB
- SHA256:
- e27c5101d50433d4b21b2cadf4271d6ecec8fe04f33210ba0f7e1b36f046cea4
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