Text Classification
Transformers
TensorFlow
ONNX
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use tarekziade/topic_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tarekziade/topic_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tarekziade/topic_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tarekziade/topic_classification") model = AutoModelForSequenceClassification.from_pretrained("tarekziade/topic_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from tarekziade/topic_classification: direct link, hf CLI and curl.
- Browser
- Download file 51.2 MB
-
https://huggingface.co/tarekziade/topic_classification/resolve/main/tf_model.h5
- Command line
-
hf download hf://tarekziade/topic_classification/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/tarekziade/topic_classification/resolve/main/tf_model.h5
51.2 MB
- Xet hash:
- efc7d9566a4cc36a61aae14bb9e292424ba2affe68a8d8d91d46fdedc4645b2b
- Size of remote file:
- 51.2 MB
- SHA256:
- decfe12b70109af8215318fbc5150e8effb55949fa9897ce23981bbbaf6844ba
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