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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4418815626d180ba1971bdfa011a7d3b313ad25f1bec9122b3d3ff19ff8e290
- Size of remote file:
- 268 MB
- SHA256:
- e15dc05a848ca084c5437ca298fad6a1c9c1106c29a160934afb44cec1d87d2b
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