Instructions to use dgalik/emoBank_test1_epoch20_batch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dgalik/emoBank_test1_epoch20_batch16 with Transformers:
# Load model directly from transformers import AutoTokenizer, DistilBertForMultiOutputRegression tokenizer = AutoTokenizer.from_pretrained("dgalik/emoBank_test1_epoch20_batch16") model = DistilBertForMultiOutputRegression.from_pretrained("dgalik/emoBank_test1_epoch20_batch16") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41fc18f885c55bc40d09355c6090b97870c47f75c71ffee16e4c9304e74d668a
- Size of remote file:
- 4.03 kB
- SHA256:
- 2e68113a05ebaef91fd4d8df1450b71cf651c4bf0f8a04a8195315a88fe06352
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