Instructions to use CLMBR/passive-lstm-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/passive-lstm-1 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/passive-lstm-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2518560/training_args.bin from CLMBR/passive-lstm-1: direct link, hf CLI and curl.
- Browser
- Download file 4.22 kB
-
https://huggingface.co/CLMBR/passive-lstm-1/resolve/c632fc42e209568984d956f432cf6cc5788ed320/checkpoint-2518560/training_args.bin
- Command line
-
hf download hf://CLMBR/passive-lstm-1@c632fc42e209568984d956f432cf6cc5788ed320/checkpoint-2518560/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/passive-lstm-1/resolve/c632fc42e209568984d956f432cf6cc5788ed320/checkpoint-2518560/training_args.bin
4.22 kB
- Xet hash:
- 203e85f2fe676c884d2abae12ba4209816bac132d20bb5f9ec65fce72e1ff045
- Size of remote file:
- 4.22 kB
- SHA256:
- 9c706f49aeb9dbf3c5699bddcaafdb9a55f7a38d20c2038f37bb44c0a536334e
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