Instructions to use CLMBR/old-existential-there-quantifier-lstm-3 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-3 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-3", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7961257151e969d92cb112bee8bd90885ea8bf9ff7cdc60a61753a63574e3227
- Size of remote file:
- 4.28 kB
- SHA256:
- aa5566700adbc39dc4c3a72c08c840322412755dbcca6ea369f420b0d3783b9d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.