Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Mofe/emotiscan_model_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mofe/emotiscan_model_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mofe/emotiscan_model_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mofe/emotiscan_model_2") model = AutoModelForSequenceClassification.from_pretrained("Mofe/emotiscan_model_2") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
pytorch_model.bin
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runs/Mar31_21-49-04_watgpu208/events.out.tfevents.1711921748.watgpu208.4065456.0
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