Instructions to use dgalik/emoBank_test2_epoch20_batch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dgalik/emoBank_test2_epoch20_batch16 with Transformers:
# Load model directly from transformers import AutoTokenizer, DistilBertForMultiOutputRegression tokenizer = AutoTokenizer.from_pretrained("dgalik/emoBank_test2_epoch20_batch16") model = DistilBertForMultiOutputRegression.from_pretrained("dgalik/emoBank_test2_epoch20_batch16") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ac43a84f9b4073ee2312f6688acd5bf35b89bb1688119a43662b65c2ae47662
- Size of remote file:
- 268 MB
- SHA256:
- 127561fae525b47ca60f62d0569182cc7d8d054cd763e31e39d43eb43382ce8f
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