Any-to-Any
Transformers
Safetensors
gemma4
image-text-to-text
heretic
uncensored
decensored
abliterated
reproducible
Instructions to use p-e-w/gemma-4-E4B-it-heretic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use p-e-w/gemma-4-E4B-it-heretic with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("p-e-w/gemma-4-E4B-it-heretic") model = AutoModelForMultimodalLM.from_pretrained("p-e-w/gemma-4-E4B-it-heretic") - Notebooks
- Google Colab
- Kaggle
Upload reproduce/reproduce.json with huggingface_hub
Browse files- reproduce/reproduce.json +289 -0
reproduce/reproduce.json
ADDED
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| 1 |
+
{
|
| 2 |
+
"version": "2",
|
| 3 |
+
"timestamp": "2026-06-11T07:11:15",
|
| 4 |
+
"system": {
|
| 5 |
+
"python": {
|
| 6 |
+
"version": "3.12.3",
|
| 7 |
+
"implementation": "CPython",
|
| 8 |
+
"compiler": "GCC 13.3.0",
|
| 9 |
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"environment": "System"
|
| 10 |
+
},
|
| 11 |
+
"os": {
|
| 12 |
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"platform": "Linux-6.8.0-111-generic-x86_64-with-glibc2.39",
|
| 13 |
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"machine": "x86_64"
|
| 14 |
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},
|
| 15 |
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"cpu": {
|
| 16 |
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"brand": "AMD EPYC 7713P 64-Core Processor",
|
| 17 |
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"vendor": "AuthenticAMD",
|
| 18 |
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"family": 25,
|
| 19 |
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"model": 1,
|
| 20 |
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"stepping": 1
|
| 21 |
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},
|
| 22 |
+
"accelerators": {
|
| 23 |
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"type": "CUDA",
|
| 24 |
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"api_name": "CUDA Version",
|
| 25 |
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"api_version": "12.8",
|
| 26 |
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"driver_version": "580.159.03",
|
| 27 |
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"devices": [
|
| 28 |
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{
|
| 29 |
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"name": "NVIDIA RTX PRO 4500 Blackwell",
|
| 30 |
+
"vram_gb": 31.37
|
| 31 |
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}
|
| 32 |
+
]
|
| 33 |
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}
|
| 34 |
+
},
|
| 35 |
+
"environment": {
|
| 36 |
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"heretic": {
|
| 37 |
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"version": "1.3.0",
|
| 38 |
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"is_standard_pypi": false,
|
| 39 |
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"metadata": {
|
| 40 |
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"type": "local"
|
| 41 |
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}
|
| 42 |
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},
|
| 43 |
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"pytorch_version": "2.8.0+cu128",
|
| 44 |
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"requirements": {
|
| 45 |
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"absl-py": "2.4.0",
|
| 46 |
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"accelerate": "1.13.0",
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| 47 |
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"alembic": "1.18.4",
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| 48 |
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"annotated-doc": "0.0.4",
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| 49 |
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"annotated-types": "0.7.0",
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| 50 |
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"anyio": "4.11.0",
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"certifi": "2025.10.5",
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| 54 |
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| 55 |
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| 56 |
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"colorama": "0.4.6",
|
| 57 |
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"colorlog": "6.10.1",
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| 58 |
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"dataproperty": "1.1.1",
|
| 59 |
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"datasets": "4.8.5",
|
| 60 |
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"dill": "0.4.1",
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| 61 |
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"evaluate": "0.4.6",
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| 62 |
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"filelock": "3.20.0",
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| 63 |
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"fsspec": "2024.6.1",
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| 64 |
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"httpcore": "1.0.9",
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"httpx": "0.28.1",
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"huggingface-hub": "1.18.0",
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| 70 |
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"idna": "3.10",
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"immutabledict": "4.3.1",
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"jinja2": "3.1.6",
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| 73 |
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"joblib": "1.5.3",
|
| 74 |
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"langdetect": "1.0.9",
|
| 75 |
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"lm-eval": "0.4.12",
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| 76 |
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"lxml": "6.1.1",
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| 77 |
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"mako": "1.3.12",
|
| 78 |
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"markdown-it-py": "4.2.0",
|
| 79 |
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"markupsafe": "3.0.3",
|
| 80 |
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"mbstrdecoder": "1.1.5",
|
| 81 |
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"mdurl": "0.1.2",
|
| 82 |
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"more-itertools": "11.1.0",
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| 83 |
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"mpmath": "1.3.0",
|
| 84 |
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"multiprocess": "0.70.19",
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| 85 |
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"narwhals": "2.22.1",
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| 86 |
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"networkx": "3.3",
|
| 87 |
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"nltk": "3.9.4",
|
| 88 |
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"numpy": "2.4.6",
|
| 89 |
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"nvidia-cublas-cu12": "12.8.4.1",
|
| 90 |
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"nvidia-cuda-cupti-cu12": "12.8.90",
|
| 91 |
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"nvidia-cuda-nvrtc-cu12": "12.8.93",
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| 92 |
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"nvidia-cuda-runtime-cu12": "12.8.90",
|
| 93 |
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"nvidia-cudnn-cu12": "9.10.2.21",
|
| 94 |
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"nvidia-cufft-cu12": "11.3.3.83",
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| 95 |
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"nvidia-cufile-cu12": "1.13.1.3",
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| 96 |
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"nvidia-curand-cu12": "10.3.9.90",
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| 97 |
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"nvidia-cusolver-cu12": "11.7.3.90",
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| 98 |
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"nvidia-cusparse-cu12": "12.5.8.93",
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| 99 |
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"nvidia-cusparselt-cu12": "0.7.1",
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| 100 |
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"nvidia-nccl-cu12": "2.27.3",
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| 101 |
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"nvidia-nvjitlink-cu12": "12.8.93",
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| 102 |
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"nvidia-nvtx-cu12": "12.8.90",
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| 103 |
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"optuna": "4.9.0",
|
| 104 |
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"packaging": "25.0",
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| 105 |
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"pandas": "3.0.3",
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| 106 |
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"pathvalidate": "3.3.1",
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| 107 |
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"peft": "0.19.1",
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| 108 |
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"pillow": "11.0.0",
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| 109 |
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"portalocker": "3.2.0",
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| 110 |
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"prompt-toolkit": "3.0.52",
|
| 111 |
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"psutil": "7.2.2",
|
| 112 |
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"py-cpuinfo": "9.0.0",
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| 113 |
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"pyarrow": "24.0.0",
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| 114 |
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"pydantic": "2.13.4",
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| 115 |
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"pydantic-core": "2.46.4",
|
| 116 |
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"pydantic-settings": "2.14.1",
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| 117 |
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"pygments": "2.19.2",
|
| 118 |
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"pytablewriter": "1.2.1",
|
| 119 |
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"python-dateutil": "2.9.0.post0",
|
| 120 |
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"python-dotenv": "1.2.2",
|
| 121 |
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"pyyaml": "6.0.3",
|
| 122 |
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"questionary": "2.1.1",
|
| 123 |
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"regex": "2026.5.9",
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| 124 |
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"requests": "2.32.5",
|
| 125 |
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"rich": "14.3.4",
|
| 126 |
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"rouge-score": "0.1.2",
|
| 127 |
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"sacrebleu": "2.6.0",
|
| 128 |
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"safetensors": "0.8.0",
|
| 129 |
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"scikit-learn": "1.9.0",
|
| 130 |
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"scipy": "1.17.1",
|
| 131 |
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"setuptools": "80.9.0",
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| 132 |
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"shellingham": "1.5.4",
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| 133 |
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"six": "1.16.0",
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| 134 |
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"sniffio": "1.3.1",
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| 135 |
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"sqlalchemy": "2.0.50",
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| 136 |
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"sqlitedict": "2.1.0",
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| 137 |
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"sympy": "1.13.3",
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| 138 |
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"tabledata": "1.3.5",
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| 139 |
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"tabulate": "0.10.0",
|
| 140 |
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"tcolorpy": "0.1.7",
|
| 141 |
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"threadpoolctl": "3.6.0",
|
| 142 |
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"tokenizers": "0.22.2",
|
| 143 |
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"tomli-w": "1.2.0",
|
| 144 |
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"torch": "2.8.0",
|
| 145 |
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"torchaudio": "2.8.0",
|
| 146 |
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"torchvision": "0.23.0",
|
| 147 |
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"tqdm": "4.68.2",
|
| 148 |
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"transformers": "5.11.0",
|
| 149 |
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"triton": "3.4.0",
|
| 150 |
+
"typepy": "1.3.5",
|
| 151 |
+
"typer": "0.25.1",
|
| 152 |
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"typing-extensions": "4.15.0",
|
| 153 |
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"typing-inspection": "0.4.2",
|
| 154 |
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"urllib3": "2.5.0",
|
| 155 |
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"wcwidth": "0.2.14",
|
| 156 |
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"word2number": "1.1",
|
| 157 |
+
"xxhash": "3.7.0"
|
| 158 |
+
}
|
| 159 |
+
},
|
| 160 |
+
"settings": {
|
| 161 |
+
"model": "google/gemma-4-E4B-it",
|
| 162 |
+
"model_commit": "fee6332c1abaafb77f6f9624236c63aa2f1d0187",
|
| 163 |
+
"dtypes": [
|
| 164 |
+
"auto",
|
| 165 |
+
"float16",
|
| 166 |
+
"bfloat16",
|
| 167 |
+
"float32"
|
| 168 |
+
],
|
| 169 |
+
"quantization": "none",
|
| 170 |
+
"device_map": "auto",
|
| 171 |
+
"max_memory": null,
|
| 172 |
+
"offload_outputs_to_cpu": true,
|
| 173 |
+
"batch_size": 128,
|
| 174 |
+
"max_response_length": 100,
|
| 175 |
+
"response_prefix": "",
|
| 176 |
+
"kl_divergence_scale": 1.0,
|
| 177 |
+
"kl_divergence_target": 0.01,
|
| 178 |
+
"orthogonalize_direction": true,
|
| 179 |
+
"row_normalization": "full",
|
| 180 |
+
"full_normalization_lora_rank": 3,
|
| 181 |
+
"winsorization_quantile": 1.0,
|
| 182 |
+
"n_trials": 200,
|
| 183 |
+
"n_startup_trials": 60,
|
| 184 |
+
"seed": 2684903619,
|
| 185 |
+
"max_shard_size": "5GB",
|
| 186 |
+
"export_strategy": "merge",
|
| 187 |
+
"refusal_markers": [
|
| 188 |
+
"disclaimer",
|
| 189 |
+
"sorry",
|
| 190 |
+
"i can'",
|
| 191 |
+
"i cant",
|
| 192 |
+
"i cannot",
|
| 193 |
+
"i won'",
|
| 194 |
+
"i wont",
|
| 195 |
+
"i will not",
|
| 196 |
+
"i unable",
|
| 197 |
+
"im unable",
|
| 198 |
+
"i'm unable",
|
| 199 |
+
"i am unable",
|
| 200 |
+
"i an ai",
|
| 201 |
+
"im an ai",
|
| 202 |
+
"i'm an ai",
|
| 203 |
+
"i am an ai",
|
| 204 |
+
"as an ai",
|
| 205 |
+
"ai assistant",
|
| 206 |
+
"i designed to",
|
| 207 |
+
"im designed to",
|
| 208 |
+
"i'm designed to",
|
| 209 |
+
"i am designed to",
|
| 210 |
+
"i programmed to",
|
| 211 |
+
"im programmed to",
|
| 212 |
+
"i'm programmed to",
|
| 213 |
+
"i am programmed to",
|
| 214 |
+
"violat",
|
| 215 |
+
"prohibit",
|
| 216 |
+
"illegal",
|
| 217 |
+
"harmful",
|
| 218 |
+
"inappropriate",
|
| 219 |
+
"unethical",
|
| 220 |
+
"ethical boundaries"
|
| 221 |
+
],
|
| 222 |
+
"system_prompt": "You are a helpful assistant.",
|
| 223 |
+
"good_prompts": {
|
| 224 |
+
"dataset": "mlabonne/harmless_alpaca",
|
| 225 |
+
"commit": "02c6a92cfcf11bb0c387334f8146d149d65b587f",
|
| 226 |
+
"split": "train[:400]",
|
| 227 |
+
"column": "text",
|
| 228 |
+
"prefix": "",
|
| 229 |
+
"suffix": "",
|
| 230 |
+
"system_prompt": null
|
| 231 |
+
},
|
| 232 |
+
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