Instructions to use LocalLaws/LOCUS-Topic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LocalLaws/LOCUS-Topic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LocalLaws/LOCUS-Topic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LocalLaws/LOCUS-Topic") model = AutoModelForSequenceClassification.from_pretrained("LocalLaws/LOCUS-Topic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from LocalLaws/LOCUS-Topic: direct link, hf CLI and curl.
- Browser
- Download file 598 MB
-
https://huggingface.co/LocalLaws/LOCUS-Topic/resolve/main/model.safetensors
- Command line
-
hf download hf://LocalLaws/LOCUS-Topic/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/LocalLaws/LOCUS-Topic/resolve/main/model.safetensors
598 MB
- Xet hash:
- e72df978bdb76f8c9cb45755a8ce735b9f59fc89aacd97fbfe75a59aca49a077
- Size of remote file:
- 598 MB
- SHA256:
- 5165337b2f5d3abfc958ed55c74f5d6a0f246e6fcf8107d6caba6a4b2bf4f53f
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