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
Download NOTICE from larkooo/gemma-e2b-rlcd: direct link, hf CLI and curl.
- Browser
- Download file 579 Bytes
-
https://huggingface.co/larkooo/gemma-e2b-rlcd/resolve/main/NOTICE
- Command line
-
hf download hf://larkooo/gemma-e2b-rlcd/NOTICE
-
curl -L -o NOTICE https://huggingface.co/larkooo/gemma-e2b-rlcd/resolve/main/NOTICE
579 Bytes
| Gemma E2B RLCD combines a Gemma 4 E2B checkpoint with a parallel decision-scoring runtime. | |
| Gemma 4 E2B was created by Google DeepMind. Its Apache 2.0 license is retained in MODEL_LICENSE. | |
| The 4-bit MLX conversion is from mlx-community/gemma-4-e2b-it-4bit at revision 238767527555cb75a05732a84dff5d6ba0dd6809. Checkpoint files are reproduced unchanged. Source revisions and hashes are recorded in checkpoint-provenance.json. | |
| The runtime code is from Larkooo/gemma-e2b-rlcd and is licensed under MIT; see LICENSE. Additional third-party notices appear in THIRD_PARTY_NOTICES.md. | |