Text Classification
Transformers
PyTorch
Safetensors
Enawené-Nawé
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use GRPUI/sgugit-classification-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GRPUI/sgugit-classification-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GRPUI/sgugit-classification-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GRPUI/sgugit-classification-model") model = AutoModelForSequenceClassification.from_pretrained("GRPUI/sgugit-classification-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e17e4fbc2b47b280852c9602fca1ab201e8cadf6258ca6c447a30cf8518360ba
- Size of remote file:
- 2.56 MB
- SHA256:
- b048853498a8f0d259e0b5123f05de34f6a2bcbdd56004a4c9da8f37a7cea60a
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