Instructions to use CLMBR/old-full-lstm-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/old-full-lstm-4 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-full-lstm-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-76319/pytorch_model.bin from CLMBR/old-full-lstm-4: direct link, hf CLI and curl.
- Browser
- Download file 272 MB
-
https://huggingface.co/CLMBR/old-full-lstm-4/resolve/main/checkpoint-76319/pytorch_model.bin
- Command line
-
hf download hf://CLMBR/old-full-lstm-4/checkpoint-76319/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CLMBR/old-full-lstm-4/resolve/main/checkpoint-76319/pytorch_model.bin
272 MB
- Xet hash:
- c3df2a5d832e0386e6e49833f04074e46e7e42da290ceda6bb241a00bce81218
- Size of remote file:
- 272 MB
- SHA256:
- 4435684ed71ee54b67a0dc6f1501cdad87f54d773755d6d8cff9892e6cdba4f7
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