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sakthai-coder-browser/.eval_results/benchmark-20260731_052122.yaml
ModelHub XC 1f0de01f6b 初始化项目,由ModelHub XC社区提供模型
Model: Nanthasit/sakthai-coder-browser
Source: Original Platform
2026-08-26 10:56:17 +08:00

94 lines
3.2 KiB
YAML

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.