Instructions to use CLMBR/old-existential-there-quantifier-lstm-0 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-0 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2671200/training_args.bin from CLMBR/old-existential-there-quantifier-lstm-0: direct link, hf CLI and curl.
- Browser
- Download file 4.28 kB
-
https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-0/resolve/main/checkpoint-2671200/training_args.bin
- Command line
-
hf download hf://CLMBR/old-existential-there-quantifier-lstm-0/checkpoint-2671200/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-0/resolve/main/checkpoint-2671200/training_args.bin
4.28 kB
- Xet hash:
- 8fec3729483721f75d3971d39f7fa589f3fa66ecb8d8ff289cf5e81e6c55d3aa
- Size of remote file:
- 4.28 kB
- SHA256:
- a3e3eb8a427aa6ef675b3efa896ef92149dab35027ddc3642d85a8279f543e6d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.