Fix missing quant_method value

[kylesayrs]

Purpose

• Fix bug where quantization_config is present but quant_method is missing, causing HF transformers to fail to parse

FAILED tests/llmcompressor/transformers/finetune/test_oneshot_then_finetune.py::TestOneshotThenFinetune::test_oneshot_then_finetune - ValueError: The model's quantization config from the arguments has no `quant_method` attribute. Make sure that the model has been correctly quantized

malformed_config.json

{
  "_name_or_path": "/home/ksayers/.cache/huggingface/hub/models--Xenova--llama2.c-stories15M/snapshots/ccdd47c2dc554aeecd2bb4e713e1c988f206a296",
  "architectures": [
    "LlamaForCausalLM"
  ],
  "attention_bias": false,
  "attention_dropout": 0.0,
  "bos_token_id": 1,
  "eos_token_id": 2,
  "head_dim": 48,
  "hidden_act": "silu",
  "hidden_size": 288,
  "initializer_range": 0.02,
  "intermediate_size": 768,
  "max_position_embeddings": 256,
  "mlp_bias": false,
  "model_type": "llama",
  "num_attention_heads": 6,
  "num_hidden_layers": 6,
  "num_key_value_heads": 6,
  "pretraining_tp": 1,
  "quantization_config": {
    "version": "0.6.0.20240928"
  },
  "rms_norm_eps": 1e-05,
  "rope_scaling": null,
  "rope_theta": 10000.0,
  "tie_word_embeddings": false,
  "torch_dtype": "float32",
  "transformers_version": "4.45.0",
  "use_cache": true,
  "vocab_size": 32000
}

corrected_config.json

{
  "_name_or_path": "/home/ksayers/.cache/huggingface/hub/models--Xenova--llama2.c-stories15M/snapshots/ccdd47c2dc554aeecd2bb4e713e1c988f206a296",
  "architectures": [
    "LlamaForCausalLM"
  ],
  "attention_bias": false,
  "attention_dropout": 0.0,
  "bos_token_id": 1,
  "eos_token_id": 2,
  "head_dim": 48,
  "hidden_act": "silu",
  "hidden_size": 288,
  "initializer_range": 0.02,
  "intermediate_size": 768,
  "max_position_embeddings": 256,
  "mlp_bias": false,
  "model_type": "llama",
  "num_attention_heads": 6,
  "num_hidden_layers": 6,
  "num_key_value_heads": 6,
  "pretraining_tp": 1,
  "quantization_config": {
    "version": "0.6.0.20240928"
    "quant_method": "compressed-tensors"
  },
  "rms_norm_eps": 1e-05,
  "rope_scaling": null,
  "rope_theta": 10000.0,
  "tie_word_embeddings": false,
  "torch_dtype": "float32",
  "transformers_version": "4.45.0",
  "use_cache": true,
  "vocab_size": 32000
}

Changes

• Always write metadata (version, quant_method) if either the quantization config or sparsity config is present
• Handle logic to unwrap these metadata fields when parsing

Testing

• tests/llmcompressor/transformers/finetune/test_oneshot_then_finetune.py no longer raises missing quant_method error