Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use juliensimon/sagemaker-distilbert-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use juliensimon/sagemaker-distilbert-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="juliensimon/sagemaker-distilbert-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("juliensimon/sagemaker-distilbert-emotion") model = AutoModelForSequenceClassification.from_pretrained("juliensimon/sagemaker-distilbert-emotion") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eceb322575fd6e11223bce03f717a663f85ab8d186bb862032d79dbe5911a06c
- Size of remote file:
- 2.99 kB
- SHA256:
- 4a4a9d9ed2ca763873ff89ba5fa3f52676a36deb3b8839f3868dbd0f37ce4e27
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