Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Prezily/topic_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prezily/topic_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Prezily/topic_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Prezily/topic_classification") model = AutoModelForSequenceClassification.from_pretrained("Prezily/topic_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9834ee4710554df22e47d92a7ef1dbea041260c978f9e52fb7d99abca2f8832
- Size of remote file:
- 438 MB
- SHA256:
- e107629af65baeda9847aa854abd0abb0fbd92831d219e948cff4799a23eac46
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