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] huggingface-cli download --local-dir gemma-e2b-rlcd larkooo/gemma-e2b-rlcd
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download examples/text.json from larkooo/gemma-e2b-rlcd: direct link, hf CLI and curl.
- Browser
- Download file 471 Bytes
-
https://huggingface.co/larkooo/gemma-e2b-rlcd/resolve/main/examples/text.json
- Command line
-
hf download hf://larkooo/gemma-e2b-rlcd/examples/text.json
-
curl -L -o text.json https://huggingface.co/larkooo/gemma-e2b-rlcd/resolve/main/examples/text.json
471 Bytes
| { | |
| "state": {"text": "A cat sleeps on the sofa. No dogs are present."}, | |
| "questions": { | |
| "animal": { | |
| "type": "choice", | |
| "instructions": "Which animal is present?", | |
| "criteria": {"cat": "A cat", "dog": "A dog", "other": "Neither a cat nor a dog"} | |
| }, | |
| "presence": { | |
| "type": "independent", | |
| "instructions": "Which animals are present in the state?", | |
| "criteria": {"cat": "A cat is present", "dog": "A dog is present"} | |
| } | |
| } | |
| } | |