Text Classification
Transformers
TensorBoard
Safetensors
bert
suhaeng
10class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use suhaeng/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suhaeng/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="suhaeng/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("suhaeng/model_output") model = AutoModelForSequenceClassification.from_pretrained("suhaeng/model_output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e1da5e6ec3347c957650589c599e4cd9aedad62eae6fe8398e2a74e9082f58c
- Size of remote file:
- 5.18 kB
- SHA256:
- 0cf2a55338d833cd99a30574023f703ac99c0b133a2ce6ed5fac2faba0f27252
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