Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use IsaacZhy/bert-base-goemotions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IsaacZhy/bert-base-goemotions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IsaacZhy/bert-base-goemotions")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IsaacZhy/bert-base-goemotions") model = AutoModelForSequenceClassification.from_pretrained("IsaacZhy/bert-base-goemotions") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13278555856e3da5db9b36891bddce58f760b512ac53a15b5b90fcd4885423b0
- Size of remote file:
- 438 MB
- SHA256:
- 04bacc2087cd98f03031374c08216b6e63f8e36f0f74513939f1c5826e92466d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.