Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcelcastrobr/sagemaker-distilbert-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcelcastrobr/sagemaker-distilbert-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcelcastrobr/sagemaker-distilbert-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcelcastrobr/sagemaker-distilbert-emotion") model = AutoModelForSequenceClassification.from_pretrained("marcelcastrobr/sagemaker-distilbert-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23b04c679830b2eab26ee4922a9de8de35d3dd7a2280ac128741d8b50c26893a
- Size of remote file:
- 2.99 kB
- SHA256:
- 83a7bc18343977bdda6111a610b9a9a1711792e5068318fbbfd6bd1928d4ffef
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