Instructions to use CLMBR/old-existential-there-quantifier-lstm-4 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-4 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2442240/scheduler.pt from CLMBR/old-existential-there-quantifier-lstm-4: direct link, hf CLI and curl.
- Browser
- Download file 627 Bytes
-
https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-4/resolve/main/checkpoint-2442240/scheduler.pt
- Command line
-
hf download hf://CLMBR/old-existential-there-quantifier-lstm-4/checkpoint-2442240/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-4/resolve/main/checkpoint-2442240/scheduler.pt
627 Bytes
- Xet hash:
- 3dae24ac268fb0102f55f436b6b1dcef7c7d04e77876d31c7adbfa149e2bb3c9
- Size of remote file:
- 627 Bytes
- SHA256:
- 8732f6b430c23914228867f21b5d74bb5d97db0fa6b45e86d0694dec16f1a57c
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