Instructions to use CLMBR/passive-lstm-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/passive-lstm-3 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/passive-lstm-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-1068480/training_args.bin from CLMBR/passive-lstm-3: direct link, hf CLI and curl.
- Browser
- Download file 4.22 kB
-
https://huggingface.co/CLMBR/passive-lstm-3/resolve/main/checkpoint-1068480/training_args.bin
- Command line
-
hf download hf://CLMBR/passive-lstm-3/checkpoint-1068480/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/passive-lstm-3/resolve/main/checkpoint-1068480/training_args.bin
4.22 kB
- Xet hash:
- 7b6394909f22afd869d371d02903e51c2b7b9992f71699164d60561a86794fa0
- Size of remote file:
- 4.22 kB
- SHA256:
- f485c4c2ab3401c9479671ea35a2d2e97980fad654dadfafe0c01d25d1a1b848
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