Instructions to use CLMBR/binding-case-lstm-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/binding-case-lstm-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/binding-case-lstm-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-76320/pytorch_model.bin from CLMBR/binding-case-lstm-2: direct link, hf CLI and curl.
- Browser
- Download file 272 MB
-
https://huggingface.co/CLMBR/binding-case-lstm-2/resolve/41ac7fd5cebc7a19f72bc6b00b4b10e69a87635b/checkpoint-76320/pytorch_model.bin
- Command line
-
hf download hf://CLMBR/binding-case-lstm-2@41ac7fd5cebc7a19f72bc6b00b4b10e69a87635b/checkpoint-76320/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CLMBR/binding-case-lstm-2/resolve/41ac7fd5cebc7a19f72bc6b00b4b10e69a87635b/checkpoint-76320/pytorch_model.bin
272 MB
- Xet hash:
- 4fab79278eb0b4cadb29c333c0659455bfbdbcb3ea2209aa4540202aa34fdc45
- Size of remote file:
- 272 MB
- SHA256:
- af2027dcad89aa1350e5ae18ac8c4a6ac59d6ca65fa43e49121bd5a77d813a5d
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