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README.md

@@ -42,6 +42,7 @@ TODO：以下由Qwen2.5-Omni-3B依赖，引入路径未知，需要去除
 ```python
 >>> from transformers import AutoModelForCausalLM, AutoProcessor
 >>> model = AutoModelForCausalLM.from_pretrained("zhoukz/MiDashengLM-HF-dev", trust_remote_code=True)
+>>> model.eval()
 >>> processor = AutoProcessor.from_pretrained("zhoukz/MiDashengLM-HF-dev", trust_remote_code=True)
 
 >>> import torchaudio
@@ -49,8 +50,9 @@ TODO：以下由Qwen2.5-Omni-3B依赖，引入路径未知，需要去除
 >>> assert sr == 16000
 >>> text = ["<|im_start|>system\\nYou are a helpful language and speech assistant.<|im_end|>\\n<|im_start|>user\\nCaption the audio<|audio_bos|><|AUDIO|><|audio_eos|><|im_end|>\\n<|im_start|>assistant\\n'"]
 
->>> model_inputs = processor(text=text, audio=audio)
->>> output = model.generate(**model_inputs)
+>>> with torch.no_grad():
+...     model_inputs = processor(text=text, audio=audio)
+...     output = model.generate(**model_inputs)
 >>> print(output)
 ["An engine is idling.'"]
 ```

modeling_midashenglm.py

@@ -667,8 +667,6 @@ class DashengQwen25OmniModelInstruct(PreTrainedModel):
         subsample_factor = config.subsample_factor
         use_encoderattention_mask = config.use_encoderattention_mask
         resize_tokenizer = True
-        lora_r = 8
-        lora_target_modules = ("q_proj", "v_proj")
         force_fp32 = False
 
         from transformers.models.qwen2_5_omni import (