Instructions to use CLMBR/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/existential-there-quantifier-lstm-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/existential-there-quantifier-lstm-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2747520/trainer_state.json from CLMBR/existential-there-quantifier-lstm-2: direct link, hf CLI and curl.
- Browser
- Download file 672 kB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/main/checkpoint-2747520/trainer_state.json
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-2/checkpoint-2747520/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/main/checkpoint-2747520/trainer_state.json
672 kB
File too large to display, you can check the raw version instead.