Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ghosttech/distilbert-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghosttech/distilbert-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ghosttech/distilbert-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ghosttech/distilbert-emotion") model = AutoModelForSequenceClassification.from_pretrained("ghosttech/distilbert-emotion") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c13f760d6ac1b92ec4a7bdc43d9413e3de7a80fab4e5f634194eea76071634c5
- Size of remote file:
- 5.3 kB
- SHA256:
- 74193330a618327f7d428dddc8d25ddacdbe422c65c58eddd849557f6fa1c94a
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