fix some errors due to inconsistency of model cards

Former-commit-id: dd83265b9b8768eb8732f59ace128dfe4aac1c47

src/llamafactory/chat/hf_engine.py

@@ -168,7 +168,7 @@ class HuggingfaceEngine(BaseEngine):
         for key, value in mm_inputs.items():
             value = value if isinstance(value, torch.Tensor) else torch.tensor(value)
             gen_kwargs[key] = value.to(model.device)
-            
+
         return gen_kwargs, prompt_length
 
     @staticmethod

src/llamafactory/extras/constants.py

@@ -1164,12 +1164,12 @@ register_model_group(
 
 register_model_group(
     models={
-        "Pixtral-12B": {
+        "Pixtral-12B-Instruct": {
             DownloadSource.DEFAULT: "mistral-community/pixtral-12b",
             DownloadSource.MODELSCOPE: "AI-ModelScope/pixtral-12b",
         }
     },
-    template="mistral",
+    template="pixtral",
     vision=True
 )
 

src/llamafactory/model/model_utils/visual.py

@@ -92,12 +92,10 @@ def autocast_projector_dtype(model: "PreTrainedModel", model_args: "ModelArgumen
 
     if getattr(model, "quantization_method", None):
         model_type = getattr(model.config, "model_type", None)
-        if model_type in ["llava", "llava_next", "llava_next_video", "paligemma", "video_llava"]:
+        if model_type in ["llava", "llava_next", "llava_next_video", "paligemma", "pixtral", "video_llava"]:
             mm_projector: "torch.nn.Module" = getattr(model, "multi_modal_projector")
         elif model_type == "qwen2_vl":
             mm_projector: "torch.nn.Module" = getattr(getattr(model, "visual"), "merger")
-        elif model_type == "pixtral":
-            mm_projector: "torch.nn.Module" = getattr(model, "vision_language_adapte")
         else:
             return
 
@@ -133,7 +131,6 @@ def get_forbidden_modules(config: "PretrainedConfig", finetuning_args: "Finetuni
     if model_type in ["llava", "llava_next", "llava_next_video", "paligemma", "pixtral", "video_llava"]:
         if finetuning_args.freeze_vision_tower:
             forbidden_modules.add("vision_tower")
-            forbidden_modules.add("vision_encoder")
 
         if finetuning_args.train_mm_proj_only:
             forbidden_modules.add("language_model")