Instructions to use ShengdingHu/compacter_t5-base_mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShengdingHu/compacter_t5-base_mnli with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ShengdingHu/compacter_t5-base_mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1cd13bed336cc57e27ae0eb9d94f63799704c5ed96a07451b27176e9873444d
- Size of remote file:
- 879 kB
- SHA256:
- e1197f490805829f9996c2ed47189589f85fe4d84144e2aec8036c60aa249171
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.