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:
- c93664ca94e584fb6980131f52346daf491e2fd9876946ac980891800b9c9c61
- Size of remote file:
- 4.03 kB
- SHA256:
- f129c121069e818e2bc4d07bce77f7e0b2d331e2a384af6dbf9818ed862b8c7d
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