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 reports/native-json-validation.json from larkooo/gemma-e2b-rlcd: direct link, hf CLI and curl.
- Browser
- Download file 67.8 kB
-
https://huggingface.co/larkooo/gemma-e2b-rlcd/resolve/main/reports/native-json-validation.json
- Command line
-
hf download hf://larkooo/gemma-e2b-rlcd/reports/native-json-validation.json
-
curl -L -o native-json-validation.json https://huggingface.co/larkooo/gemma-e2b-rlcd/resolve/main/reports/native-json-validation.json
67.8 kB
| { | |
| "scope": "Fixed local regression cases, not general multimodal accuracy or calibration proof. One measured run per path per case.", | |
| "cases": [ | |
| { | |
| "name": "skunks", | |
| "expected": { | |
| "Baby skunks": 5, | |
| "Dog": 1 | |
| }, | |
| "result": { | |
| "answers": { | |
| "Baby skunks": { | |
| "calibration_status": "unvalidated", | |
| "temperature": 1.0, | |
| "probability_source": "restricted_json_value_likelihoods", | |
| "diagnostics": { | |
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| "9": 0.0023754464162451497 | |
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| "legend": { | |
| "0": "0 baby skunks", | |
| "1": "1 baby skunks", | |
| "2": "2 baby skunks", | |
| "3": "3 baby skunks", | |
| "4": "4 baby skunks", | |
| "5": "5 baby skunks", | |
| "6": "6 baby skunks", | |
| "7": "7 baby skunks", | |
| "8": "8 baby skunks", | |
| "9": "9 baby skunks" | |
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| "5": 8.176388481262041e-05, | |
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| "0": "0 dogs", | |
| "1": "1 dogs", | |
| "2": "2 dogs", | |
| "3": "3 dogs", | |
| "4": "4 dogs", | |
| "5": "5 dogs", | |
| "6": "6 dogs", | |
| "7": "7 dogs", | |
| "8": "8 dogs", | |
| "9": "9 dogs" | |
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| "inference_seconds": 1.4461837910057511, | |
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| "cache": "Fresh input KV and media features for every run; ordinary output-token KV caching remains enabled for normal generation.", | |
| "answers": "Normal Gemma generates one JSON object for all fields, greedily, without thinking. Compare choice names, most likely grade levels, and booleans at a 50% threshold. The scorer also returns probability distributions and expected grades. Agreement is not an accuracy measurement." | |
| } | |
| } | |
| }, | |
| { | |
| "name": "text", | |
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| "presence": { | |
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| "animal": { | |
| "calibration_status": "unvalidated", | |
| "temperature": 1.0, | |
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| "cat": 0.9999999926955352, | |
| "dog": 6.383844089613385e-09, | |
| "horse": 9.206206440074525e-10 | |
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| "selected_probability": 0.9999999926955352 | |
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| "count": { | |
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| "temperature": 1.0, | |
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| "0": 12.217308044433594, | |
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| "0": 7.530662585853558e-05, | |
| "1": 2.8244037711623705e-06, | |
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| "3": 2.406712349138733e-07 | |
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| "0": "Zero", | |
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| "3": "Three" | |
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| "noul": 5.218091726916857e-07 | |
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| "type": "independent", | |
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| "inference_seconds": 0.27812479200656526, | |
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| "raw_text": "{\"animal\": \"cat\", \"count\": 2, \"dog\": false, \"presence\": {\"cat\": true, \"dog\": false}}", | |
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| "model": "Same resident Gemma 4 E2B 4-bit weights; float32 compute; all 35 layers", | |
| "timing": "One run per path, parallel scorer first, normal generation second. Includes input preparation and inference; shared upload decoding added equally to each path. Excludes model loading, upload transfer, and allocator reset. No warm-up runs; first-use effects and run order can affect this observation.", | |
| "cache": "Fresh input KV and media features for every run; ordinary output-token KV caching remains enabled for normal generation.", | |
| "answers": "Normal Gemma generates one JSON object for all fields, greedily, without thinking. Compare choice names, most likely grade levels, and booleans at a 50% threshold. The scorer also returns probability distributions and expected grades. Agreement is not an accuracy measurement." | |
| } | |
| } | |
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| { | |
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| "Report": 1.4468828238803991e-15 | |
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| "type": "choice", | |
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| "conditioning": "shared complete question schema; no previous field answers" | |
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| "normal": { | |
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| "raw_text": "{\"document\": \"Invoice\", \"currency\": \"USD\", \"paid\": false}", | |
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| "agreement": { | |
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| "model": "Same resident Gemma 4 E2B 4-bit weights; float32 compute; all 35 layers", | |
| "timing": "One run per path, parallel scorer first, normal generation second. Includes input preparation and inference; shared upload decoding added equally to each path. Excludes model loading, upload transfer, and allocator reset. No warm-up runs; first-use effects and run order can affect this observation.", | |
| "cache": "Fresh input KV and media features for every run; ordinary output-token KV caching remains enabled for normal generation.", | |
| "answers": "Normal Gemma generates one JSON object for all fields, greedily, without thinking. Compare choice names, most likely grade levels, and booleans at a 50% threshold. The scorer also returns probability distributions and expected grades. Agreement is not an accuracy measurement." | |
| } | |
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| { | |
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| "intent": "Cancel", | |
| "timing": "End of this month", | |
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| "2": 0.0024318760318991664, | |
| "3": 0.000863685426060581, | |
| "4": 0.0014895362854541818, | |
| "5": 0.0010067121486512969, | |
| "6": 0.00027520141403579993, | |
| "7": 0.0002307829950513383, | |
| "8": 0.0005852688675128792, | |
| "9": 0.0029362740830353746 | |
| }, | |
| "type": "score", | |
| "score": 1.0426847647267505, | |
| "legend": { | |
| "0": "0 dogs", | |
| "1": "1 dogs", | |
| "2": "2 dogs", | |
| "3": "3 dogs", | |
| "4": "4 dogs", | |
| "5": "5 dogs", | |
| "6": "6 dogs", | |
| "7": "7 dogs", | |
| "8": "8 dogs", | |
| "9": "9 dogs" | |
| } | |
| } | |
| }, | |
| "inference_seconds": 3.170949292019941, | |
| "execution": { | |
| "execution": "shared_json_prefix_gpu_batched_fields", | |
| "prefix_prefills": 1, | |
| "prefix_tokens": 2436, | |
| "primitive_fields": 2, | |
| "question_suffix_tokens": [ | |
| 6, | |
| 4 | |
| ], | |
| "candidate_token_lengths": [ | |
| [ | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1 | |
| ], | |
| [ | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1 | |
| ] | |
| ], | |
| "preprocess_seconds": 0.6641687910014298, | |
| "prefill_seconds": 2.471621042001061, | |
| "branch_seconds": 0.03497962499386631, | |
| "branch_batch_sizes": [ | |
| 2 | |
| ], | |
| "candidate_batch_sizes": [], | |
| "compute_dtype": "float32", | |
| "kv_storage": "replicated_per_batch_row", | |
| "conditioning": "shared complete question schema; no previous field answers" | |
| }, | |
| "valid": true, | |
| "total_seconds": 3.170949292019941 | |
| }, | |
| "comparison": { | |
| "seconds": { | |
| "parallel": 3.170949292019941, | |
| "normal": 3.328362667001784 | |
| }, | |
| "normal_over_parallel": 1.0496423501246115, | |
| "parallel_values": { | |
| "Baby skunks": 5, | |
| "Dog": 1 | |
| }, | |
| "normal": { | |
| "answers": { | |
| "Baby skunks": 5, | |
| "Dog": 1 | |
| }, | |
| "raw_text": "{\"Baby skunks\": 5, \"Dog\": 1}", | |
| "valid": true, | |
| "error": null, | |
| "finish_reason": "stop", | |
| "input_tokens": 2436, | |
| "output_tokens": 15, | |
| "max_output_tokens": 128, | |
| "preprocess_seconds": 0.653564042004291, | |
| "generation_seconds": 2.6747562079981435, | |
| "inference_seconds": 3.328362667001784, | |
| "total_seconds": 3.328362667001784 | |
| }, | |
| "agreement": { | |
| "Baby skunks": true, | |
| "Dog": true | |
| }, | |
| "methodology": { | |
| "model": "Same resident Gemma 4 E2B 4-bit weights; float32 compute; all 35 layers", | |
| "timing": "One run per path, parallel scorer first, normal generation second. Includes input preparation and inference; shared upload decoding added equally to each path. Excludes model loading, upload transfer, and allocator reset. No warm-up runs; first-use effects and run order can affect this observation.", | |
| "cache": "Fresh input KV and media features for every run; ordinary output-token KV caching remains enabled for normal generation.", | |
| "answers": "Normal Gemma generates one JSON object for all fields, greedily, without thinking. Compare choice names, most likely grade levels, and booleans at a 50% threshold. The scorer also returns probability distributions and expected grades. Agreement is not an accuracy measurement." | |
| } | |
| } | |
| } | |
| ] | |
| } | |