Text Classification
Transformers
TensorBoard
Safetensors
bert
lsb_ais5
categorical
multi_label
10_class
Generated from Trainer
text-embeddings-inference
Instructions to use SBzz/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SBzz/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SBzz/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SBzz/model_output") model = AutoModelForSequenceClassification.from_pretrained("SBzz/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5a4f31c079314798931a3b6a752cce38a08e6725c460aa05d77b615aa663e44
- Size of remote file:
- 5.18 kB
- SHA256:
- 25916c53a9c8dc2cac94149a27c54ccd6e9f6e0bd2a42ba2a434f4ee77566378
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