Instructions to use LocalLaws/LOCUS-Function with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LocalLaws/LOCUS-Function with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LocalLaws/LOCUS-Function")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LocalLaws/LOCUS-Function") model = AutoModelForSequenceClassification.from_pretrained("LocalLaws/LOCUS-Function", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from LocalLaws/LOCUS-Function: direct link, hf CLI and curl.
- Browser
- Download file 598 MB
-
https://huggingface.co/LocalLaws/LOCUS-Function/resolve/main/model.safetensors
- Command line
-
hf download hf://LocalLaws/LOCUS-Function/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/LocalLaws/LOCUS-Function/resolve/main/model.safetensors
598 MB
- Xet hash:
- 37b9279d8ac0d2bb31319ef8d6657154fef5ff7720b1f8c3bd88269e078a19b6
- Size of remote file:
- 598 MB
- SHA256:
- cbb87e7fa9a7e0c109fae2f1932fa443452db80b21c6c580758972532fd64d80
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