inference/log.txt

[2025-09-15 09:15:42,098] [INFO] [real_accelerator.py:222:get_accelerator] Setting ds_accelerator to cuda (auto detect)
LOAD_VISION_EARLY is set
FORCE_NO_DOWNSAMPLE is set
VIDEO_RESIZE is set as 0x64, 0, 64
HIGHRES_BASE is set as 0x32, 0, 32
MAXRES is set as 1536
MINRES is set as 0
VIDEO_MAXRES is set as 480
VIDEO_MINRES is set as 288
PAD2STRIDE is set
LOWRES_RESIZE is set as 384x32
Loading OlaQwen3ForCausalLM model...
Loading BEATs Model
Missing keys: ['model.speech_encoder.whisper_model.positional_embedding', 'model.speech_encoder.whisper_model.conv1.weight', 'model.speech_encoder.whisper_model.conv1.bias', 'model.speech_encoder.whisper_model.conv2.weight', 'model.speech_encoder.whisper_model.conv2.bias', 'model.speech_encoder.whisper_model.blocks.0.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.0.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.0.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.0.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.0.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.0.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.0.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.0.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.0.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.0.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.0.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.0.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.0.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.0.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.0.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.1.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.1.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.1.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.1.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.1.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.1.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.1.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.1.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.1.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.1.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.1.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.1.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.1.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.1.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.1.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.2.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.2.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.2.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.2.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.2.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.2.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.2.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.2.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.2.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.2.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.2.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.2.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.2.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.2.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.2.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.3.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.3.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.3.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.3.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.3.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.3.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.3.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.3.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.3.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.3.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.3.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.3.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.3.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.3.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.3.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.4.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.4.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.4.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.4.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.4.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.4.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.4.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.4.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.4.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.4.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.4.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.4.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.4.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.4.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.4.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.5.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.5.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.5.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.5.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.5.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.5.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.5.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.5.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.5.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.5.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.5.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.5.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.5.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.5.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.5.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.6.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.6.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.6.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.6.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.6.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.6.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.6.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.6.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.6.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.6.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.6.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.6.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.6.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.6.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.6.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.7.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.7.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.7.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.7.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.7.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.7.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.7.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.7.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.7.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.7.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.7.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.7.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.7.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.7.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.7.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.8.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.8.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.8.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.8.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.8.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.8.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.8.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.8.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.8.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.8.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.8.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.8.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.8.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.8.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.8.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.9.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.9.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.9.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.9.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.9.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.9.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.9.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.9.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.9.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.9.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.9.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.9.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.9.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.9.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.9.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.10.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.10.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.10.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.10.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.10.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.10.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.10.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.10.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.10.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.10.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.10.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.10.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.10.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.10.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.10.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.11.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.11.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.11.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.11.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.11.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.11.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.11.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.11.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.11.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.11.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.11.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.11.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.11.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.11.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.11.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.12.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.12.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.12.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.12.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.12.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.12.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.12.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.12.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.12.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.12.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.12.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.12.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.12.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.12.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.12.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.13.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.13.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.13.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.13.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.13.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.13.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.13.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.13.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.13.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.13.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.13.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.13.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.13.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.13.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.13.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.14.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.14.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.14.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.14.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.14.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.14.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.14.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.14.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.14.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.14.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.14.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.14.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.14.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.14.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.14.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.15.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.15.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.15.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.15.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.15.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.15.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.15.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.15.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.15.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.15.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.15.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.15.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.15.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.15.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.15.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.16.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.16.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.16.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.16.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.16.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.16.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.16.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.16.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.16.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.16.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.16.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.16.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.16.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.16.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.16.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.17.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.17.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.17.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.17.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.17.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.17.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.17.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.17.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.17.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.17.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.17.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.17.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.17.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.17.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.17.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.18.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.18.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.18.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.18.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.18.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.18.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.18.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.18.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.18.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.18.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.18.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.18.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.18.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.18.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.18.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.19.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.19.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.19.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.19.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.19.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.19.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.19.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.19.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.19.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.19.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.19.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.19.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.19.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.19.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.19.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.20.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.20.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.20.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.20.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.20.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.20.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.20.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.20.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.20.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.20.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.20.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.20.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.20.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.20.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.20.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.21.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.21.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.21.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.21.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.21.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.21.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.21.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.21.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.21.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.21.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.21.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.21.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.21.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.21.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.21.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.22.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.22.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.22.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.22.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.22.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.22.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.22.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.22.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.22.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.22.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.22.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.22.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.22.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.22.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.22.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.23.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.23.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.23.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.23.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.23.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.23.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.23.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.23.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.23.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.23.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.23.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.23.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.23.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.23.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.23.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.24.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.24.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.24.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.24.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.24.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.24.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.24.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.24.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.24.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.24.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.24.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.24.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.24.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.24.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.24.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.25.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.25.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.25.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.25.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.25.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.25.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.25.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.25.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.25.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.25.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.25.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.25.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.25.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.25.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.25.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.26.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.26.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.26.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.26.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.26.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.26.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.26.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.26.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.26.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.26.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.26.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.26.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.26.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.26.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.26.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.27.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.27.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.27.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.27.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.27.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.27.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.27.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.27.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.27.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.27.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.27.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.27.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.27.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.27.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.27.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.28.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.28.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.28.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.28.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.28.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.28.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.28.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.28.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.28.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.28.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.28.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.28.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.28.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.28.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.28.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.29.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.29.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.29.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.29.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.29.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.29.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.29.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.29.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.29.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.29.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.29.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.29.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.29.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.29.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.29.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.30.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.30.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.30.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.30.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.30.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.30.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.30.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.30.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.30.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.30.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.30.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.30.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.30.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.30.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.30.mlp_ln.bias', 'model.speech_encoder.whisper_model.blocks.31.attn.query.weight', 'model.speech_encoder.whisper_model.blocks.31.attn.query.bias', 'model.speech_encoder.whisper_model.blocks.31.attn.key.weight', 'model.speech_encoder.whisper_model.blocks.31.attn.value.weight', 'model.speech_encoder.whisper_model.blocks.31.attn.value.bias', 'model.speech_encoder.whisper_model.blocks.31.attn.out.weight', 'model.speech_encoder.whisper_model.blocks.31.attn.out.bias', 'model.speech_encoder.whisper_model.blocks.31.attn_ln.weight', 'model.speech_encoder.whisper_model.blocks.31.attn_ln.bias', 'model.speech_encoder.whisper_model.blocks.31.mlp.0.weight', 'model.speech_encoder.whisper_model.blocks.31.mlp.0.bias', 'model.speech_encoder.whisper_model.blocks.31.mlp.2.weight', 'model.speech_encoder.whisper_model.blocks.31.mlp.2.bias', 'model.speech_encoder.whisper_model.blocks.31.mlp_ln.weight', 'model.speech_encoder.whisper_model.blocks.31.mlp_ln.bias', 'model.speech_encoder.whisper_model.ln_post.weight', 'model.speech_encoder.whisper_model.ln_post.bias', 'model.speech_encoder.beats_model.post_extract_proj.weight', 'model.speech_encoder.beats_model.post_extract_proj.bias', 'model.speech_encoder.beats_model.patch_embedding.weight', 'model.speech_encoder.beats_model.encoder.pos_conv.0.bias', 'model.speech_encoder.beats_model.encoder.pos_conv.0.weight_g', 'model.speech_encoder.beats_model.encoder.pos_conv.0.weight_v', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn.grep_a', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn.relative_attention_bias.weight', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn.k_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn.k_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn.v_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn.v_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn.q_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn.q_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn.out_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn.out_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn.grep_linear.weight', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn.grep_linear.bias', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.0.self_attn_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.0.fc1.weight', 'model.speech_encoder.beats_model.encoder.layers.0.fc1.bias', 'model.speech_encoder.beats_model.encoder.layers.0.fc2.weight', 'model.speech_encoder.beats_model.encoder.layers.0.fc2.bias', 'model.speech_encoder.beats_model.encoder.layers.0.final_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.0.final_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn.grep_a', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn.k_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn.k_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn.v_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn.v_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn.q_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn.q_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn.out_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn.out_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn.grep_linear.weight', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn.grep_linear.bias', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn.relative_attention_bias.weight', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.1.self_attn_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.1.fc1.weight', 'model.speech_encoder.beats_model.encoder.layers.1.fc1.bias', 'model.speech_encoder.beats_model.encoder.layers.1.fc2.weight', 'model.speech_encoder.beats_model.encoder.layers.1.fc2.bias', 'model.speech_encoder.beats_model.encoder.layers.1.final_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.1.final_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn.grep_a', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn.k_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn.k_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn.v_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn.v_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn.q_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn.q_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn.out_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn.out_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn.grep_linear.weight', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn.grep_linear.bias', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn.relative_attention_bias.weight', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.2.self_attn_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.2.fc1.weight', 'model.speech_encoder.beats_model.encoder.layers.2.fc1.bias', 'model.speech_encoder.beats_model.encoder.layers.2.fc2.weight', 'model.speech_encoder.beats_model.encoder.layers.2.fc2.bias', 'model.speech_encoder.beats_model.encoder.layers.2.final_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.2.final_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn.grep_a', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn.k_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn.k_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn.v_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn.v_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn.q_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn.q_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn.out_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn.out_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn.grep_linear.weight', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn.grep_linear.bias', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn.relative_attention_bias.weight', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.3.self_attn_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.3.fc1.weight', 'model.speech_encoder.beats_model.encoder.layers.3.fc1.bias', 'model.speech_encoder.beats_model.encoder.layers.3.fc2.weight', 'model.speech_encoder.beats_model.encoder.layers.3.fc2.bias', 'model.speech_encoder.beats_model.encoder.layers.3.final_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.3.final_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn.grep_a', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn.k_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn.k_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn.v_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn.v_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn.q_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn.q_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn.out_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn.out_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn.grep_linear.weight', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn.grep_linear.bias', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn.relative_attention_bias.weight', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.4.self_attn_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.4.fc1.weight', 'model.speech_encoder.beats_model.encoder.layers.4.fc1.bias', 'model.speech_encoder.beats_model.encoder.layers.4.fc2.weight', 'model.speech_encoder.beats_model.encoder.layers.4.fc2.bias', 'model.speech_encoder.beats_model.encoder.layers.4.final_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.4.final_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn.grep_a', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn.k_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn.k_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn.v_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn.v_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn.q_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn.q_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn.out_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn.out_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn.grep_linear.weight', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn.grep_linear.bias', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn.relative_attention_bias.weight', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.5.self_attn_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.5.fc1.weight', 'model.speech_encoder.beats_model.encoder.layers.5.fc1.bias', 'model.speech_encoder.beats_model.encoder.layers.5.fc2.weight', 'model.speech_encoder.beats_model.encoder.layers.5.fc2.bias', 'model.speech_encoder.beats_model.encoder.layers.5.final_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.5.final_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn.grep_a', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn.k_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn.k_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn.v_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn.v_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn.q_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn.q_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn.out_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn.out_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn.grep_linear.weight', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn.grep_linear.bias', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn.relative_attention_bias.weight', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.6.self_attn_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.6.fc1.weight', 'model.speech_encoder.beats_model.encoder.layers.6.fc1.bias', 'model.speech_encoder.beats_model.encoder.layers.6.fc2.weight', 'model.speech_encoder.beats_model.encoder.layers.6.fc2.bias', 'model.speech_encoder.beats_model.encoder.layers.6.final_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.6.final_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn.grep_a', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn.k_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn.k_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn.v_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn.v_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn.q_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn.q_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn.out_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn.out_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn.grep_linear.weight', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn.grep_linear.bias', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn.relative_attention_bias.weight', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.7.self_attn_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.7.fc1.weight', 'model.speech_encoder.beats_model.encoder.layers.7.fc1.bias', 'model.speech_encoder.beats_model.encoder.layers.7.fc2.weight', 'model.speech_encoder.beats_model.encoder.layers.7.fc2.bias', 'model.speech_encoder.beats_model.encoder.layers.7.final_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.7.final_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn.grep_a', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn.k_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn.k_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn.v_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn.v_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn.q_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn.q_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn.out_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn.out_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn.grep_linear.weight', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn.grep_linear.bias', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn.relative_attention_bias.weight', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.8.self_attn_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.8.fc1.weight', 'model.speech_encoder.beats_model.encoder.layers.8.fc1.bias', 'model.speech_encoder.beats_model.encoder.layers.8.fc2.weight', 'model.speech_encoder.beats_model.encoder.layers.8.fc2.bias', 'model.speech_encoder.beats_model.encoder.layers.8.final_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.8.final_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn.grep_a', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn.k_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn.k_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn.v_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn.v_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn.q_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn.q_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn.out_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn.out_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn.grep_linear.weight', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn.grep_linear.bias', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn.relative_attention_bias.weight', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.9.self_attn_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.9.fc1.weight', 'model.speech_encoder.beats_model.encoder.layers.9.fc1.bias', 'model.speech_encoder.beats_model.encoder.layers.9.fc2.weight', 'model.speech_encoder.beats_model.encoder.layers.9.fc2.bias', 'model.speech_encoder.beats_model.encoder.layers.9.final_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.9.final_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn.grep_a', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn.k_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn.k_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn.v_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn.v_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn.q_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn.q_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn.out_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn.out_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn.grep_linear.weight', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn.grep_linear.bias', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn.relative_attention_bias.weight', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.10.self_attn_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.10.fc1.weight', 'model.speech_encoder.beats_model.encoder.layers.10.fc1.bias', 'model.speech_encoder.beats_model.encoder.layers.10.fc2.weight', 'model.speech_encoder.beats_model.encoder.layers.10.fc2.bias', 'model.speech_encoder.beats_model.encoder.layers.10.final_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.10.final_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn.grep_a', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn.k_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn.k_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn.v_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn.v_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn.q_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn.q_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn.out_proj.weight', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn.out_proj.bias', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn.grep_linear.weight', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn.grep_linear.bias', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn.relative_attention_bias.weight', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.11.self_attn_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layers.11.fc1.weight', 'model.speech_encoder.beats_model.encoder.layers.11.fc1.bias', 'model.speech_encoder.beats_model.encoder.layers.11.fc2.weight', 'model.speech_encoder.beats_model.encoder.layers.11.fc2.bias', 'model.speech_encoder.beats_model.encoder.layers.11.final_layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layers.11.final_layer_norm.bias', 'model.speech_encoder.beats_model.encoder.layer_norm.weight', 'model.speech_encoder.beats_model.encoder.layer_norm.bias', 'model.speech_encoder.beats_model.layer_norm.weight', 'model.speech_encoder.beats_model.layer_norm.bias', 'model.speech_encoder.beats_model.predictor.weight', 'model.speech_encoder.beats_model.predictor.bias', 'model.speech_projector.speech_newline', 'model.speech_projector.speech_begin', 'model.speech_projector.speech_end', 'model.speech_projector.linear1.weight', 'model.speech_projector.linear1.bias', 'model.speech_projector.linear2.weight', 'model.speech_projector.linear2.bias']
Unexpected keys: []
Loading vision tower...
Loading vision tower succeeded.
User: Hello, who are you?
Assistant: Hello! I'm PLM-V, an AI assistant created to provide information, answer questions, and help with various tasks. How can I assist you today?

================================================================================
🧪 开始多模态推理测试
================================================================================

============================================================
🧪 测试: Pure Text
📝 问题: Hello, who are you? Please introduce yourself briefly.
============================================================
<|im_start|>system
You are PLM-V, a helpful assistant.<|im_end|>
<|im_start|>user
Hello, who are you? Please introduce yourself briefly.<|im_end|>
<|im_start|>assistant
 Hello! I am PLM-V, an intelligent assistant designed to provide you with detailed and accurate information, answer questions, and assist with a wide range of topics. My goal is to support you in a friendly and knowledgeable manner, making your interactions with me as informative and helpful as possible. How can I assist you today?
✅ 推理成功!
🤖 回复: Hello! I am PLM-V, an intelligent assistant designed to provide you with detailed and accurate information, answer questions, and assist with a wide range of topics. My goal is to support you in a friendly and knowledgeable manner, making your interactions with me as informative and helpful as possible. How can I assist you today?

============================================================
🧪 测试: Text & Image (Visual only)
📝 问题: <image>
Please describe this image in detail.
============================================================
dynamic ViT batch size: 13
<|im_start|>system
You are PLM-V, a helpful assistant.<|im_end|>
<|im_start|>user
<image>
Please describe this image in detail.<|im_end|>
<|im_start|>assistant
 The image shows a close-up of a red panda, characterized by its distinctive reddish-brown fur with white markings around its face and back. The red panda appears to be leaning on a wooden structure, possibly a ledge or a part of a platform. The subject has a mix of black and white fur around its ears, eyes, and muzzle, which contrasts with its redder head. The expression on the red panda's face seems calm and curious as it looks directly at the camera. The background features blurred greenery, suggesting that the animal is in an outdoor environment with trees and plants. The setting gives a natural, outdoor feel to the image.
✅ 推理成功!
🤖 回复: The image shows a close-up of a red panda, characterized by its distinctive reddish-brown fur with white markings around its face and back. The red panda appears to be leaning on a wooden structure, possibly a ledge or a part of a platform. The subject has a mix of black and white fur around its ears, eyes, and muzzle, which contrasts with its redder head. The expression on the red panda's face seems calm and curious as it looks directly at the camera. The background features blurred greenery, suggesting that the animal is in an outdoor environment with trees and plants. The setting gives a natural, outdoor feel to the image.

============================================================
🔄 准备Speech相关测试 (可能输出乱码，因为speech部分未训练)
============================================================

📥 加载视频数据...
✅ 视频加载成功:
  - 视频帧数: 8
  - 视频像素值形状: torch.Size([8, 3, 448, 448])
  - 每帧patch数: [1, 1, 1, 1, 1, 1, 1, 1]

📥 加载音频数据...
✅ 音频加载成功:
  - mel谱图形状: torch.Size([2, 3000, 128])
  - 音频长度: tensor([3000, 3000])
  - 音频块数: tensor([2])
  - 原始音频波形形状: torch.Size([2, 480000])

============================================================
🧪 测试: Audio only (预期乱码)
📝 问题: <speech>
Please transcribe and summarize what you heard in the audio.
============================================================
speech batch size: 2
<|im_start|>system
You are PLM-V, a helpful assistant.<|im_end|>
<|im_start|>user
<speech>
Please transcribe and summarize what you heard in the audio.<|im_end|>
<|im_start|>assistant
 The end

The internet

or

or

structure

The overcorrection

As年人

pre-hel theorem is the following: suppose that the other
There is no one knows that the

We consider that the following is the
It is sufficient that the

Consider that the

As we see the answer to the question

Let us consider the following: 
The initial

or, in the beginning of the text

We need to consider the following: 

The answer is

Here, we need to consider the following answers

However, the question is: What is the
But the answer to the question is: 
Or the sequence of the answer is: 

The final answer that is: 

Actually, the factor, and the issue is: The problem is: 
The problem solved, and the answer is: 

However, the problem that is: The problem posed is: For the final solution

The answer to the question is: For the following question

But the question that is solved by: The issue here is: The question we need to solve: The problem we are considering: The question that exists: The problem that we need to address: The question that is: 

Let us consider the following: The problem that was

The answer is: The problem is: 

We reconsider the question: The question now

The problem is: The question we have: The problem that follows: The question is: The final question: The problem that exists: The problem that is: The question posed

The final answer is: The problem: The question considered: The question posed: The final answer: The problem that we consider: The problem that was solved: The answer: The problem solved: The problem solved:

After a moment of reflection, the question, and the problem is: The question, and the problem is: The answer to the problem: The question and the problem is: The problem that the question is: The problem where the question is

However, the initial question, and the answer following these lines:

Alternatively, the problem is solved by the following question: 
The sequence of the question and answers

The problem posed in the following
After some thought,the sequence: The problem that the system

The actual problem: The actual answer to the question: The actual issue that is: The actual thing that is: The actual fact that is: The actual solution to the problem: The actual moment: The actual thing: The actual purpose: The actual issue: The actual event: The actual time: The actual issue resolved: The actual thing that is: The actual thing that is: The actual moment that is: The actual situation

The end of the answer is: The end of the process is: The end of the procedure is
The end of the process that is: 

The final answer is: The final step in the process is: The final part of the procedure is:
The final note that is: The final issue is: The final issue that is:
The final step is: The final issue solved is: The final part of the question is: The final question is: The final version of the question is: The final part of the structure is: The final structure that is: The final structure of the problem is: The final structure of the consideration is: The final consideration of the structure is: The structure that is: The structure that contains the

But the final answer is: The final answer to the question: The final answer that is: The final answer: The final answer: The final answer: The final answer: The final answer:

The final issue is: The final answer: The initial issue is:

The final answer
So, the final answer is: The final answer

Suppose we consider the final answer: The final answer is: The final answer

The final answer is: The final answer
The final answer
The final answer
The final answer

The final answer is: The final answer

The final answer is: The final answer

The final answer is: The final answer: The final answer: The final answer
But the final answer to the question is: The final answer: The final answer: The final answer:
The final answer: The final answer

The final answer

The final answer is: The final answer

The final solution is: The final answer

The final answer

The final answer is: The final answer

The final answer

The final step is: The final answer

The final answer

The final answer

The final answer is: The final answer

The final answer: The final answer

The final answer

The final answer
The final answer
The final answer
The final answer

The final answer (a)

But the

The final answer

The final answer

The final answer

The final answer

The final answer: The final answer

The final answer

The final answer

The final answer

The final answer

The final answer

The final answer

The final answer

The final answer

The final answer

The final answer
✅ 推理成功!
🤖 回复: The end

The internet

or

or

structure

The overcorrection

As年人

pre-hel theorem is the following: suppose that the other
There is no one knows that the

We consider that the following is the
It is sufficient that the

Consider that the

As we see the answer to the question

Let us consider the following: 
The initial

or, in the beginning of the text

We need to consider the following: 

The answer is

Here, we need to consider the following answers

However, the question is: What is the
But the answer to the question is: 
Or the sequence of the answer is: 

The final answer that is: 

Actually, the factor, and the issue is: The problem is: 
The problem solved, and the answer is: 

However, the problem that is: The problem posed is: For the final solution

The answer to the question is: For the following question

But the question that is solved by: The issue here is: The question we need to solve: The problem we are considering: The question that exists: The problem that we need to address: The question that is: 

Let us consider the following: The problem that was

The answer is: The problem is: 

We reconsider the question: The question now

The problem is: The question we have: The problem that follows: The question is: The final question: The problem that exists: The problem that is: The question posed

The final answer is: The problem: The question considered: The question posed: The final answer: The problem that we consider: The problem that was solved: The answer: The problem solved: The problem solved:

After a moment of reflection, the question, and the problem is: The question, and the problem is: The answer to the problem: The question and the problem is: The problem that the question is: The problem where the question is

However, the initial question, and the answer following these lines:

Alternatively, the problem is solved by the following question: 
The sequence of the question and answers

The problem posed in the following
After some thought,the sequence: The problem that the system

The actual problem: The actual answer to the question: The actual issue that is: The actual thing that is: The actual fact that is: The actual solution to the problem: The actual moment: The actual thing: The actual purpose: The actual issue: The actual event: The actual time: The actual issue resolved: The actual thing that is: The actual thing that is: The actual moment that is: The actual situation

The end of the answer is: The end of the process is: The end of the procedure is
The end of the process that is: 

The final answer is: The final step in the process is: The final part of the procedure is:
The final note that is: The final issue is: The final issue that is:
The final step is: The final issue solved is: The final part of the question is: The final question is: The final version of the question is: The final part of the structure is: The final structure that is: The final structure of the problem is: The final structure of the consideration is: The final consideration of the structure is: The structure that is: The structure that contains the

But the final answer is: The final answer to the question: The final answer that is: The final answer: The final answer: The final answer: The final answer: The final answer:

The final issue is: The final answer: The initial issue is:

The final answer
So, the final answer is: The final answer

Suppose we consider the final answer: The final answer is: The final answer

The final answer is: The final answer
The final answer
The final answer
The final answer

The final answer is: The final answer

The final answer is: The final answer

The final answer is: The final answer: The final answer: The final answer
But the final answer to the question is: The final answer: The final answer: The final answer:
The final answer: The final answer

The final answer

The final answer is: The final answer

The final solution is: The final answer

The final answer

The final answer is: The final answer

The final answer

The final step is: The final answer

The final answer

The final answer

The final answer is: The final answer

The final answer: The final answer

The final answer

The final answer
The final answer
The final answer
The final answer

The final answer (a)

But the

The final answer

The final answer

The final answer

The final answer

The final answer: The final answer

The final answer

The final answer

The final answer

The final answer

The final answer

The final answer

The final answer

The final answer

The final answer

The final answer

============================================================
🧪 测试: Audio + Image (预期乱码)
📝 问题: <image>
User's question in speech: <speech>

============================================================
dynamic ViT batch size: 13
speech batch size: 2
<|im_start|>system
You are PLM-V, a helpful assistant.<|im_end|>
<|im_start|>user
<image>
User's question in speech: <speech>
<|im_end|>
<|im_start|>assistant
 Bicytude: 连们在考虑了的时候 - 衋体在当前的是一场关于亚的类型、以通过的是一支集
在使用后端使用相同的方式的人，可能不知道，或者，其是否在何时进入，而是一次使用相同错误地管理，可能不会发生，或可能是在之前，或者是不是还有其他相关的人，或者，或者，或是否，或，或呢，或是一个，或是一个或，或是

I don't understand the given content: 迭取到一张图片，该是关于一个文本文件，内容和类似于的功能，或者是一个关于，或者是一个的人，或若是关于一个关于学习和关于其他主题的上的行为，它是什么原因（或者，或者，或者，或？)还是关于其他主题呢，或在关于其他生物，比如，或者，或者，或者，或呢，或，我需要在使用了，或者，或者，或然呢？ - 我需要找到文件中关于“如何改进一个文本文件，以便于更趋时，或是在其他主题，或者是一个关于如何管理一个复杂的数据文件，或是在一个应用数据文件，或者一个关于如何在浏览器的“如何利用Python的自动控制中的“或，或是一个关于一个关于如何使用标签，或是一个关于其他事情，比如，或者一个关于另一个关于如何使用的或是什么，或者，或呢？等，或者？？或呢？
✅ 推理成功!
🤖 回复: Bicytude: 连们在考虑了的时候 - 衋体在当前的是一场关于亚的类型、以通过的是一支集
在使用后端使用相同的方式的人，可能不知道，或者，其是否在何时进入，而是一次使用相同错误地管理，可能不会发生，或可能是在之前，或者是不是还有其他相关的人，或者，或者，或是否，或，或呢，或是一个，或是一个或，或是

I don't understand the given content: 迭取到一张图片，该是关于一个文本文件，内容和类似于的功能，或者是一个关于，或者是一个的人，或若是关于一个关于学习和关于其他主题的上的行为，它是什么原因（或者，或者，或者，或？)还是关于其他主题呢，或在关于其他生物，比如，或者，或者，或者，或呢，或，我需要在使用了，或者，或者，或然呢？ - 我需要找到文件中关于“如何改进一个文本文件，以便于更趋时，或是在其他主题，或者是一个关于如何管理一个复杂的数据文件，或是在一个应用数据文件，或者一个关于如何在浏览器的“如何利用Python的自动控制中的“或，或是一个关于一个关于如何使用标签，或是一个关于其他事情，比如，或者一个关于另一个关于如何使用的或是什么，或者，或呢？等，或者？？或呢？

============================================================
🧪 测试: Video + Text
📝 问题: Frame1: <image>
Frame2: <image>
Frame3: <image>
Frame4: <image>
Frame5: <image>
Frame6: <image>
Frame7: <image>
Frame8: <image>
What is the red panda doing in this video? Please describe the actions and movements you observe.
============================================================
dynamic ViT batch size: 8
<|im_start|>system
You are PLM-V, a helpful assistant.<|im_end|>
<|im_start|>user
Frame1: <image>
Frame2: <image>
Frame3: <image>
Frame4: <image>
Frame5: <image>
Frame6: <image>
Frame7: <image>
Frame8: <image>
What is the red panda doing in this video? Please describe the actions and movements you observe.<|im_end|>
<|im_start|>assistant
 In this video, a red panda is climbing up a branch, perched on it while holding something in its mouth, and later sitting on the ground and reaching up towards bamboo sticks suspended from a tree. At one point, one of the red pandas chews on bamboo, and at another point, the blue creature is seen on the grassy ground, looking up towards the red panda. The scene then shows the red panda still perched on the branch, holding something in its mouth, and another red panda is perched on the ground, reaching up towards the bamboo on the tree. After a few moments, the panda on the ground finishes its activity and sits down on the grassy ground.
✅ 推理成功!
🤖 回复: In this video, a red panda is climbing up a branch, perched on it while holding something in its mouth, and later sitting on the ground and reaching up towards bamboo sticks suspended from a tree. At one point, one of the red pandas chews on bamboo, and at another point, the blue creature is seen on the grassy ground, looking up towards the red panda. The scene then shows the red panda still perched on the branch, holding something in its mouth, and another red panda is perched on the ground, reaching up towards the bamboo on the tree. After a few moments, the panda on the ground finishes its activity and sits down on the grassy ground.

================================================================================
📊 多模态推理测试总结
================================================================================
✅ PASS Pure Text       (预期: PASS    ) - 应该正常 (训练好的InternVL)
✅ PASS Text & Image    (预期: PASS    ) - 应该正常 (训练好的InternVL)
✅ PASS Video + Text    (预期: PASS    ) - 应该正常 (训练好的InternVL)
✅ PASS Audio only      (预期: GARBLED ) - 可能乱码 (speech未训练)
✅ PASS Audio + Image   (预期: GARBLED ) - 可能乱码 (speech未训练)

📈 测试统计: 5/5 通过
🎉 基础功能正常，Speech集成架构成功！
💡 Speech相关测试如果输出乱码是正常的，因为speech部分还未训练
🌟 所有基础模态测试都通过了！

=== 多模态推理测试完成 ===