Any-to-Any
MLX
Safetensors
gemma4
mlx-vlm
rlcd
multimodal
classification
parallel-inference
image-text-to-text
audio
video
4-bit precision
Instructions to use larkooo/gemma-e2b-rlcd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use larkooo/gemma-e2b-rlcd with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download larkooo/gemma-e2b-rlcd --local-dir gemma-e2b-rlcd
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 226 Bytes
53e24ca | 1 2 3 4 5 6 | """Gemma E2B RLCD: parallel multimodal classification and grading."""
from .core import Choice, DecisionEngine, Independent, Noul, Score, State
__all__ = ["Choice", "DecisionEngine", "Independent", "Noul", "Score", "State"]
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