Instructions to use CLMBR/passive-lstm-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/passive-lstm-0 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/passive-lstm-0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from CLMBR/passive-lstm-0: direct link, hf CLI and curl.
- Browser
- Download file 272 MB
-
https://huggingface.co/CLMBR/passive-lstm-0/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://CLMBR/passive-lstm-0/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CLMBR/passive-lstm-0/resolve/main/pytorch_model.bin
272 MB
- Xet hash:
- e59adfd544a9abc8b2cace856b8a303452ae5ce162ef52b42fd942fc7cef0532
- Size of remote file:
- 272 MB
- SHA256:
- 17b9d16444e284f9221e7a30acf472a9560313a4558d205b1987d1396c81778e
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