Text Classification
Transformers
Safetensors
code
bert
Generated from Trainer
text-embeddings-inference
Instructions to use HuggingFaceTB/stack-edu-classifier-c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuggingFaceTB/stack-edu-classifier-c with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HuggingFaceTB/stack-edu-classifier-c")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HuggingFaceTB/stack-edu-classifier-c") model = AutoModelForSequenceClassification.from_pretrained("HuggingFaceTB/stack-edu-classifier-c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 952a352d61462bc49799adf362cd473f2c2ab6d0eaac226db5ccab6e8d037e59
- Size of remote file:
- 5.3 kB
- SHA256:
- 9e55e559a9d4a06a6d8952a82c5cd92d5c9e1d18fcb9ab0be3a9ee807c9d41ee
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