Instructions to use mkrausio/bert-emotion-ordinal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mkrausio/bert-emotion-ordinal with Transformers:
# Load model directly from transformers import BertForMultiOutputOrdinalRegression model = BertForMultiOutputOrdinalRegression.from_pretrained("mkrausio/bert-emotion-ordinal", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mkrausio/bert-emotion-ordinal: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/mkrausio/bert-emotion-ordinal/resolve/main/training_args.bin
- Command line
-
hf download hf://mkrausio/bert-emotion-ordinal/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mkrausio/bert-emotion-ordinal/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- b4667bcd4964930831a416338361e74a0a67dcacc1538db7dff6ab04fb74df18
- Size of remote file:
- 5.3 kB
- SHA256:
- 80a84ea196e0b38c3c5f67bda5f89b16a6eda030e2c9214c3caf74804be3e74a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.