model: Nanthasit/sakthai-coder-browser
benchmark_ts: '2026-07-31T05:50:33Z'
verdict: MODEL_BROKEN_BIAS_CORRUPTION
benchmark_valid: false
backend: llama.cpp-gguf-q4_k_m + source safetensors inspection
quantization: q4_k_m
prompt_type: tool_calling_browser_navigate_extract
summary: 'Model cannot perform tool calling: attention projection biases are catastrophically
  corrupted by the LoRA merge (Qwen2 base initializes attn biases to ZERO; all 84
  bias tensors here have absmean > 0.01, layer-0 k_proj absmean 27.7 / max 354). Degenerate
  output: whitespace-loop at temp<=0.7 on all 3 seeds (0 tool calls, 0 valid JSON);
  only at temp 1.5 does it emit any text (''Hi'' on a trivial prompt). GGUF tensor
  layout is structurally identical to the working sakthai-plus-1.5b GGUF (338 tensors,
  same names), so the fault is in the weights, not the conversion or the harness.'
trials:
- seed: 7
  temp: 0.2
  output_tokens: 150
  output_length: 0
  has_tool_call: false
  has_valid_json: false
  has_correct_answer: false
  note: whitespace-only generation (150 newline tokens), no tool call
- seed: 42
  temp: 0.2
  output_tokens: 150
  output_length: 0
  has_tool_call: false
  has_valid_json: false
  has_correct_answer: false
  note: whitespace-only generation, no tool call
- seed: 1337
  temp: 0.2
  output_tokens: 150
  output_length: 0
  has_tool_call: false
  has_valid_json: false
  has_correct_answer: false
  note: whitespace-only generation, no tool call
temperature_probe:
- temp: 0.2
  prompt: full browser prompt
  result: blank/whitespace loop
- temp: 0.4
  prompt: full browser prompt
  result: blank/whitespace loop
- temp: 0.7
  prompt: full browser prompt
  result: blank/whitespace loop
- temp: 1.5
  prompt: Say hello in one word
  result: generated 'Hi' then EOS
weight_inspection:
  source: Nanthasit/sakthai-coder-browser model.safetensors (3.09 GB, 338 tensors,
    1.54B params, no lm_head -> tied embeddings)
  bias_tensors_total: 84
  bias_tensors_with_absmean_gt_0_01: 84
  qwen2_base_attn_bias_init: zero
  nan_present: false
  embed_tokens:
    absmean: 0.0136
    absmax: 0.295
    normal: true
  sample_corrupted_biases:
  - tensor: model.layers.0.self_attn.k_proj.bias
    absmean: 27.6991
    absmax: 354.0
  - tensor: model.layers.0.self_attn.q_proj.bias
    absmean: 1.1716
    absmax: 28.88
  - tensor: model.layers.1.self_attn.k_proj.bias
    absmean: 3.284
    absmax: 111.0
  - tensor: model.layers.1.self_attn.q_proj.bias
    absmean: 0.5512
    absmax: 10.62
  - tensor: model.layers.10.self_attn.k_proj.bias
    absmean: 0.3383
    absmax: 6.62
  - tensor: model.layers.14.self_attn.q_proj.bias
    absmean: 0.5422
    absmax: 13.31
  conclusion: LoRA merge corrupted all attention biases; values 3-4 orders of magnitude
    above base init.
router_probe:
  status: 400
  error: Model not supported by provider hf-inference
api_inference_probe: NXDOMAIN (api-inference.huggingface.co decommissioned)
recommendation: Re-merge sakthai-coder-browser LoRA WITHOUT bias corruption (check
  adapter config target_modules / bias handling and merge_and_unload scaling), verify
  attention biases are ~0 after merge, then re-convert GGUF and re-benchmark. Until
  then the model is not usable for inference. Model card should carry a BROKEN-WEIGHTS
  warning.