Image 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("image-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
| # 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." | |