Feature Extraction
Transformers
Safetensors
PyTorch
English
eden
text-enhancement
grammar-correction
text-rewriting
encoder-decoder
transformer
custom_code
Instructions to use Rybib/EDEN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rybib/EDEN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Rybib/EDEN", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Rybib/EDEN", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 513 Bytes
453c542 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | #!/bin/bash
# Double-click this file to chat with EDEN in a terminal window.
# It loads the published model from Hugging Face and lets you clean up text.
cd "$(dirname "$0")" || exit 1
echo "Starting EDEN..."
# Make sure the needed packages are present.
python3 -c "import transformers, torch" 2>/dev/null
if [ $? -ne 0 ]; then
echo "Installing required packages (one time)..."
pip3 install torch transformers
fi
python3 examples/try_eden.py
echo ""
echo "EDEN session ended. You can close this window."
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