Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use NPCProgrammer/DBERT_Emotions_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NPCProgrammer/DBERT_Emotions_tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NPCProgrammer/DBERT_Emotions_tuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NPCProgrammer/DBERT_Emotions_tuned") model = AutoModelForSequenceClassification.from_pretrained("NPCProgrammer/DBERT_Emotions_tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ac71c7f39446b6c5599816a12080fc154a5226f3b084ad7c23748909758abc7
- Size of remote file:
- 4.92 kB
- SHA256:
- a235f8a78e739d1c8d14af3cf3988ed6c7700974a8613e543b80f48f86c186e2
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