Instructions to use Data-Lab/ml-topics-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Data-Lab/ml-topics-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Data-Lab/ml-topics-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Data-Lab/ml-topics-classifier") model = AutoModelForSequenceClassification.from_pretrained("Data-Lab/ml-topics-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Data-Lab/ml-topics-classifier: direct link, hf CLI and curl.
- Browser
- Download file 513 MB
-
https://huggingface.co/Data-Lab/ml-topics-classifier/resolve/469c9e91b32987e664d356a074d902fc91ae90a2/model.safetensors
- Command line
-
hf download hf://Data-Lab/ml-topics-classifier@469c9e91b32987e664d356a074d902fc91ae90a2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Data-Lab/ml-topics-classifier/resolve/469c9e91b32987e664d356a074d902fc91ae90a2/model.safetensors
513 MB
- Xet hash:
- 14bcf34f127244375a33d980b7941fd51fe21171f9c41535c3aa6c8ff420ed8b
- Size of remote file:
- 513 MB
- SHA256:
- 7fb2aaed0576b56890b1bb550b1c0617a4ba0d98960153e02791ec1c36b6132c
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