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")# pip install -U transformers accelerate # 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/main/model.safetensors
- Command line
-
hf download hf://Data-Lab/ml-topics-classifier/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Data-Lab/ml-topics-classifier/resolve/main/model.safetensors
513 MB
- Xet hash:
- baaf294b2249a33b4869dbff4285d73005dd0cfa750e5c9bcda0c8c9a8c0da07
- Size of remote file:
- 513 MB
- SHA256:
- e36ff4225a1c4210f1b2897d1b9fb12ee6774aab8f947ac4de6b6603f9d33f80
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