Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Manirathinam21/bert_emo_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Manirathinam21/bert_emo_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Manirathinam21/bert_emo_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Manirathinam21/bert_emo_classifier") model = AutoModelForSequenceClassification.from_pretrained("Manirathinam21/bert_emo_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eaf5753bcac1f26dd9d7f58475ee520eb4e7dc1d8b10d32ee2df8a16b01e96f3
- Size of remote file:
- 438 MB
- SHA256:
- 588d099d94f1c675789964220d48af6482a594a0fa66f535b28c3ca852473654
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