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: 1,066 Bytes
53e24ca | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | {
"scope": "Browser integration checks after installing the workload examples. Timings are individual observations, not pooled with the repeated benchmark.",
"presets_checked": {
"support_matrix": 28,
"inbox_matrix": 32,
"ticket_flags": 32,
"catalog_choices": 4
},
"initial_check": {
"complete": true,
"comparison_rows": 28,
"different_fields": [
"public_status_page_incident",
"assigned_agent_tier"
],
"parallel_seconds": 2.456,
"normal_seconds": 12.004,
"issue": "Browser editor materialized different default yes/no meanings than the benchmark."
},
"fix": "Presets now include the core default yes/no meanings explicitly. A regression test verifies the complete generated task matches each benchmark case after editor-style serialization.",
"final_check": {
"complete": true,
"comparison_rows": 28,
"different_fields": [],
"parallel_seconds": 3.407,
"normal_seconds": 8.573,
"console_errors": []
},
"tests": "89 passed; lint and JavaScript syntax checks passed."
}
|