Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use dimboump/glue_sst_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dimboump/glue_sst_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dimboump/glue_sst_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dimboump/glue_sst_classifier") model = AutoModelForSequenceClassification.from_pretrained("dimboump/glue_sst_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f203d86ae7103f635a3de8e8fb0dd26f568c411a899cb74e69e88c4c8e417ac
- Size of remote file:
- 3.06 kB
- SHA256:
- 1ec91a9c48e9c6c5a50ab6cbbdcf6e129f1fe484111289df8d9687127317d048
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