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 concept_memory/__init__.py from Syigen/rgcm: direct link, hf CLI and curl.
- Browser
- Download file 192 Bytes
-
https://huggingface.co/Syigen/rgcm/resolve/main/concept_memory/__init__.py
- Command line
-
hf download hf://Syigen/rgcm/concept_memory/__init__.py
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curl -L -o __init__.py https://huggingface.co/Syigen/rgcm/resolve/main/concept_memory/__init__.py
192 Bytes
| from .model import ConceptMemoryModel | |
| from .types import Criterion, Question, QuestionType, TaskOutput | |
| __all__ = ["ConceptMemoryModel", "Criterion", "Question", "QuestionType", "TaskOutput"] | |