Text Classification
Transformers
TensorFlow
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use jonaskoenig/topic_classification_02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonaskoenig/topic_classification_02 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jonaskoenig/topic_classification_02")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jonaskoenig/topic_classification_02") model = AutoModelForSequenceClassification.from_pretrained("jonaskoenig/topic_classification_02", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b96ef2a4898a92f3df8e2a5bb06eca963e8a0156a71dd05375e6479be2803bf
- Size of remote file:
- 51.2 MB
- SHA256:
- 451d90fb047fab2366d4d4ddd3a2f7286a30ed4d26756467d71f5973114740d0
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