Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use jkhan447/sentiment-model-sample-group-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jkhan447/sentiment-model-sample-group-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jkhan447/sentiment-model-sample-group-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jkhan447/sentiment-model-sample-group-emotion") model = AutoModelForSequenceClassification.from_pretrained("jkhan447/sentiment-model-sample-group-emotion") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a79af6a388ca256e0af84d96faecbd39c9c952c53c30ada0a9c8daa9b5a08b94
- Size of remote file:
- 438 MB
- SHA256:
- 04c6db4c8ce46def2e6c1097ffb01392a7e376fbd33cef6f0e71b77bd37f745a
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