Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use NPCProgrammer/BERT_Emotions_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NPCProgrammer/BERT_Emotions_tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NPCProgrammer/BERT_Emotions_tuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NPCProgrammer/BERT_Emotions_tuned") model = AutoModelForSequenceClassification.from_pretrained("NPCProgrammer/BERT_Emotions_tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32b177a01f319e54012c4c8e26334b9f12a41cafa6b40d7069381bd38010141a
- Size of remote file:
- 4.92 kB
- SHA256:
- cbb220d8190a3ef48e9deb6686f56c452b25e08f660a5126b7b7e1746f9206e3
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