Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use ThePromptKing/bert_emo_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThePromptKing/bert_emo_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ThePromptKing/bert_emo_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ThePromptKing/bert_emo_classifier") model = AutoModelForSequenceClassification.from_pretrained("ThePromptKing/bert_emo_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 837d1f9430858e533192ba2231be6b98ab96e48b4b2eef1edbe71b264da8a24c
- Size of remote file:
- 438 MB
- SHA256:
- 57de2f99ac163e77dacbf92ea89267e3c90074f2f9a786adc1bc11ab367d9c90
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