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
| [build-system] | |
| requires = ["setuptools>=68"] | |
| build-backend = "setuptools.build_meta" | |
| [project] | |
| name = "eden-text-enhancement" | |
| version = "1.0.0" | |
| description = "EDEN: a from-scratch encoder-decoder Transformer for text enhancement." | |
| readme = "README.md" | |
| requires-python = ">=3.9" | |
| license = { text = "Apache-2.0" } | |
| authors = [{ name = "Ryan Dunn" }] | |
| keywords = ["nlp", "text-enhancement", "grammar-correction", "transformer", "pytorch"] | |
| dependencies = [ | |
| "torch>=2.1", | |
| "transformers>=4.40", | |
| "tokenizers>=0.15", | |
| "safetensors>=0.4", | |
| "numpy>=1.24", | |
| "datasets>=2.16", | |
| "tqdm>=4.66", | |
| "psutil>=5.9", | |
| ] | |
| [project.scripts] | |
| eden = "eden.cli:main" | |
| [tool.setuptools] | |
| packages = ["eden"] | |