=== 2026-09-10T08:13:44-07:00 START A4B-heretic -> /tank/aimodels/G4-MeroMero-26B-A4B-it-uncensored-heretic-NVFP4A16
[notice] To update, run: python3.12 -m pip install --upgrade pip
loading /tank/aimodels/G4-MeroMero-26B-A4B-it-uncensored-heretic-bf16
Loading weights: 100%|██████████| 1013/1013 [00:00<00:00, 4035.87it/s]
building calibration (<= 512 @ seq 8192)
  512 calibration rows
NVFP4 oneshot: scheme=NVFP4A16, Linear-only, vision/audio/projector/embed/lm_head/norms kept BF16
2026-09-10T15:14:09.8205 | __init__ | WARNING - Disabling tokenizer parallelism due to threading conflict between FastTokenizer and Datasets. Set TOKENIZERS_PARALLELISM=false to suppress this warning.
2026-09-10T15:14:12.3242 | reset | INFO - Compression lifecycle reset
2026-09-10T15:14:12.8109 | apply_recipe_modifiers | WARNING - Detected an MoE model which has not been linearized. First load model `with llmcompressor.modeling.moe.linearize.load_quantizable_moe` before passing to `oneshot`. Falling back to post-load linearization.
2026-09-10T15:14:13.2653 | linearize_moe | WARNING - MoE is being linearized after loading in order to support efficient calibration of experts. However, this may be inefficient if the model checkpoint is already linearized (2D -> 3D -> 2D). Consider registering a load converter for faster load times. See https://docs.vllm.ai/projects/llm-compressor/en/latest/developer-tutorials/add-moe-support
Linearizing experts: 100%|██████████| 30/30 [00:35<00:00,  1.17s/it]
2026-09-10T15:14:48.4792 | from_modifiers | INFO - Creating recipe from modifiers
Applying quantization config: 100%|██████████| 11755/11755 [00:01<00:00, 8851.89it/s]
2026-09-10T15:14:50.3917 | initialize | INFO - Compression lifecycle initialized for 1 modifiers
2026-09-10T15:14:50.3920 | IndependentPipeline | INFO - Inferred `DataFreePipeline` for `QuantizationModifier`
2026-09-10T15:15:14.4903 | finalize | INFO - Compression lifecycle finalized for 1 modifiers
saving -> /tank/aimodels/G4-MeroMero-26B-A4B-it-uncensored-heretic-NVFP4A16
Compressing model: 100%|██████████| 11755/11755 [00:11<00:00, 980.90it/s] 
Writing model shards: 100%|██████████| 1/1 [00:08<00:00,  8.96s/it]
Dispatching model: 100%|██████████| 16828/16828 [00:00<00:00, 43870.85it/s]
DONE. serve --quantization compressed-tensors (multimodal: vision+audio kept BF16; NO --language-model-only). No spec-decode; Gemma-4 has no MTP.
=== 2026-09-10T08:15:52-07:00 END A4B-heretic rc=0 size=16G
=== 2026-09-10T08:15:52-07:00 START v2-31B-heretic -> /tank/aimodels/G4-MeroMero-v2-31B-heretic-NVFP4A16
[notice] To update, run: python3.12 -m pip install --upgrade pip
loading /tank/aimodels/G4-MeroMero-v2-31B-heretic-bf16
Traceback (most recent call last):
  File "/tank/aimodels/meromero-v2-nvfp4-work/quant_nvfp4_gemma.py", line 76, in load_model
    model = M.from_pretrained(
            ^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/modeling_utils.py", line 4283, in from_pretrained
    model = cls(config, *model_args, **model_kwargs)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/gemma4/modeling_gemma4.py", line 2452, in __init__
    self.model = Gemma4Model(config)
                 ^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/gemma4/modeling_gemma4.py", line 2132, in __init__
    language_model = AutoModel.from_config(config=config.text_config)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/auto/auto_factory.py", line 250, in from_config
    return model_class._from_config(config, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/modeling_utils.py", line 1620, in _from_config
    model = cls(config, **kwargs)
            ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/gemma4/modeling_gemma4.py", line 1605, in __init__
    [Gemma4TextDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/gemma4/modeling_gemma4.py", line 1375, in __init__
    self.self_attn = Gemma4TextAttention(config=config, layer_idx=layer_idx)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/gemma4/modeling_gemma4.py", line 1193, in __init__
    self.num_key_value_groups = config.num_attention_heads // num_key_value_heads
                                ~~~~~~~~~~~~~~~~~~~~~~~~~~~^^~~~~~~~~~~~~~~~~~~~~
TypeError: unsupported operand type(s) for //: 'int' and 'NoneType'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/tank/aimodels/meromero-v2-nvfp4-work/quant_nvfp4_gemma.py", line 128, in <module>
    sys.exit(main())
             ^^^^^^
  File "/tank/aimodels/meromero-v2-nvfp4-work/quant_nvfp4_gemma.py", line 99, in main
    model, tok = load_model(a.model)
                 ^^^^^^^^^^^^^^^^^^^
  File "/tank/aimodels/meromero-v2-nvfp4-work/quant_nvfp4_gemma.py", line 82, in load_model
    model = M.from_pretrained(
            ^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/auto/auto_factory.py", line 406, in from_pretrained
    return model_class.from_pretrained(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/modeling_utils.py", line 4283, in from_pretrained
    model = cls(config, *model_args, **model_kwargs)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/gemma4/modeling_gemma4.py", line 2452, in __init__
    self.model = Gemma4Model(config)
                 ^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/gemma4/modeling_gemma4.py", line 2132, in __init__
    language_model = AutoModel.from_config(config=config.text_config)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/auto/auto_factory.py", line 250, in from_config
    return model_class._from_config(config, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/modeling_utils.py", line 1620, in _from_config
    model = cls(config, **kwargs)
            ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/gemma4/modeling_gemma4.py", line 1605, in __init__
    [Gemma4TextDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/gemma4/modeling_gemma4.py", line 1375, in __init__
    self.self_attn = Gemma4TextAttention(config=config, layer_idx=layer_idx)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/models/gemma4/modeling_gemma4.py", line 1193, in __init__
    self.num_key_value_groups = config.num_attention_heads // num_key_value_heads
                                ~~~~~~~~~~~~~~~~~~~~~~~~~~~^^~~~~~~~~~~~~~~~~~~~~
TypeError: unsupported operand type(s) for //: 'int' and 'NoneType'
=== 2026-09-10T08:16:18-07:00 END v2-31B-heretic rc=1 size=
=== 2026-09-10T08:16:18-07:00 BATCH DONE
