Text Classification
Transformers
TensorBoard
Safetensors
bert
gjg
categorical
multi_label
10_class
Generated from Trainer
text-embeddings-inference
Instructions to use pongDang/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pongDang/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pongDang/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pongDang/model_output") model = AutoModelForSequenceClassification.from_pretrained("pongDang/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
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