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:
- d5fb3988875bb55907f41eb16985a0a82ed79896ed3c1b96a0d94b7aa2f7f9b8
- Size of remote file:
- 268 MB
- SHA256:
- 9b60ff5d4a3f639979c7de5c737eb9af355662407fd63ce8779024373cfc8f73
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