Text Classification
Transformers
TensorBoard
Safetensors
bert
Lee
10_class
Generated from Trainer
text-embeddings-inference
Instructions to use audgns/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use audgns/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="audgns/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("audgns/model_output") model = AutoModelForSequenceClassification.from_pretrained("audgns/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66dc5c4ff9a401ea5d12d92337a32a0fcd6bb24ce23199e73a8d55f2767871b1
- Size of remote file:
- 5.37 kB
- SHA256:
- b7968dc82ce0f3dae1106a1193af0faaf227d1616ff198c0a7111732608ed8a8
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