Instructions to use CLMBR/existential-there-quantifier-lstm-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/existential-there-quantifier-lstm-1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/existential-there-quantifier-lstm-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-915840/optimizer.pt from CLMBR/existential-there-quantifier-lstm-1: direct link, hf CLI and curl.
- Browser
- Download file 544 MB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-1/resolve/main/checkpoint-915840/optimizer.pt
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-1/checkpoint-915840/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CLMBR/existential-there-quantifier-lstm-1/resolve/main/checkpoint-915840/optimizer.pt
544 MB
- Xet hash:
- 50ed193a484d6096d83da424515d9d4bdb0926514635aaf46586053fb481269b
- Size of remote file:
- 544 MB
- SHA256:
- d4c642c55afd6066d24c048e9c3d8969a778860ec92eeb308f1d616e95d5dba4
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