Instructions to use SIRIS-Lab/erc-classifiers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SIRIS-Lab/erc-classifiers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SIRIS-Lab/erc-classifiers")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SIRIS-Lab/erc-classifiers") model = AutoModelForSequenceClassification.from_pretrained("SIRIS-Lab/erc-classifiers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from SIRIS-Lab/erc-classifiers: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/SIRIS-Lab/erc-classifiers/resolve/main/model.safetensors
- Command line
-
hf download hf://SIRIS-Lab/erc-classifiers/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/SIRIS-Lab/erc-classifiers/resolve/main/model.safetensors
440 MB
- Xet hash:
- dddc2b835dc3031184f5bcdbf40f5832f45ff2aa0233f282d4ff1d1be6a81e0a
- Size of remote file:
- 440 MB
- SHA256:
- 460479fca2a5f7a821d98ede2c80792d168116c96f2dacbc697f3f61b68e39fd
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