Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use anindabitm/sagemaker-distilbert-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anindabitm/sagemaker-distilbert-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anindabitm/sagemaker-distilbert-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anindabitm/sagemaker-distilbert-emotion") model = AutoModelForSequenceClassification.from_pretrained("anindabitm/sagemaker-distilbert-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7a343f4f9e245040934430d751a80765537f0fd6c225a8dcd4e718336382875
- Size of remote file:
- 268 MB
- SHA256:
- 057d01fa1666387a09be1159d630d7125b518fc1488d0881405f4b575f701b9c
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