Instructions to use ShawnyPapa77/cpeg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShawnyPapa77/cpeg with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ShawnyPapa77/cpeg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download ablations/before_patch_encoder/done.json from ShawnyPapa77/cpeg: direct link, hf CLI and curl.
- Browser
- Download file 192 Bytes
-
https://huggingface.co/ShawnyPapa77/cpeg/resolve/main/ablations/before_patch_encoder/done.json
- Command line
-
hf download hf://ShawnyPapa77/cpeg/ablations/before_patch_encoder/done.json
-
curl -L -o done.json https://huggingface.co/ShawnyPapa77/cpeg/resolve/main/ablations/before_patch_encoder/done.json
192 Bytes
| { | |
| "model": "microsoft/deberta-v3-large", | |
| "max_len": 512, | |
| "lr": 1e-05, | |
| "batch": 32, | |
| "epochs": 2, | |
| "seed": 42, | |
| "steps": 3671, | |
| "rows": 58729, | |
| "rows_mode": "unique, weighted" | |
| } | |