Text Classification
Transformers
TensorFlow
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use jonaskoenig/topic_classification_01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonaskoenig/topic_classification_01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jonaskoenig/topic_classification_01")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jonaskoenig/topic_classification_01") model = AutoModelForSequenceClassification.from_pretrained("jonaskoenig/topic_classification_01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78ee6b20a60093c88fbe3e5831756f5fd37aa83d6d7162edb54f8a387728657a
- Size of remote file:
- 51.2 MB
- SHA256:
- b8b629a9f1ad65646a4a6d6eb26168ec0be05799ea76c8eeb9e0412c7e5b5944
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