Instructions to use CLMBR/old-existential-there-quantifier-lstm-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/old-existential-there-quantifier-lstm-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-1908000/optimizer.pt from CLMBR/old-existential-there-quantifier-lstm-2: direct link, hf CLI and curl.
- Browser
- Download file 544 MB
-
https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-2/resolve/main/checkpoint-1908000/optimizer.pt
- Command line
-
hf download hf://CLMBR/old-existential-there-quantifier-lstm-2/checkpoint-1908000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-2/resolve/main/checkpoint-1908000/optimizer.pt
544 MB
- Xet hash:
- a4ef1426c37e5b91950efa2c7b2e534e219c8e19c268b3426d6a6596e739ed8d
- Size of remote file:
- 544 MB
- SHA256:
- 727fc1c8721e5fb86780de5ab8d416a018240ff82c21b5e7ccf61037671d5c9e
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