Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcelcastrobr/sagemaker-distilbert-emotion-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcelcastrobr/sagemaker-distilbert-emotion-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcelcastrobr/sagemaker-distilbert-emotion-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcelcastrobr/sagemaker-distilbert-emotion-2") model = AutoModelForSequenceClassification.from_pretrained("marcelcastrobr/sagemaker-distilbert-emotion-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5de2ab82cbbe0a5bb736bddcc4ce0ec740f41f03c6844c96d869f1608538c375
- Size of remote file:
- 268 MB
- SHA256:
- 0be4d215a4d8f7713288b58559b9bf7e76398b28b0c9ff247d1008f10a9f6ac6
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