Instructions to use Syigen/rgcm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Syigen/rgcm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Syigen/rgcm")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Syigen/rgcm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from Syigen/rgcm: direct link, hf CLI and curl.
- Browser
- Download file 343 Bytes
-
https://huggingface.co/Syigen/rgcm/resolve/main/config.json
- Command line
-
hf download hf://Syigen/rgcm/config.json
-
curl -L -o config.json https://huggingface.co/Syigen/rgcm/resolve/main/config.json
343 Bytes
| { | |
| "datasets": [ | |
| "mteb/banking77", | |
| "nyu-mll/glue:sst2", | |
| "google/boolq" | |
| ], | |
| "task_types": [ | |
| "choice", | |
| "score", | |
| "noul" | |
| ], | |
| "encoder": "sentence-transformers/all-mpnet-base-v2", | |
| "epochs": 50, | |
| "batch_size": 32, | |
| "seed": 42, | |
| "model_version": "base-20261003-171325Z", | |
| "generated_at": "2026-10-03T17:13:25Z" | |
| } | |