Delete mm_builder.py

mm_builder.py

@@ -1,33 +0,0 @@
-import torch
-from modeling_mmalaya import MMAlayaMPTForCausalLM
-from transformers import AutoTokenizer
-from mm_utils import DEFAULT_IMAGE_TOKEN
-
-
-def load_pretrained_model(model_path, device_map="auto", device="cuda"):
-    kwargs = {"device_map": device_map}
-    if device != "cuda":
-        kwargs['device_map'] = {"": device}
-    kwargs['torch_dtype'] = torch.bfloat16
-
-    print('******** load mpt model from here kwargs ', kwargs)
-    tokenizer = AutoTokenizer.from_pretrained(model_path)
-    model = MMAlayaMPTForCausalLM.from_pretrained(
-        model_path,
-        low_cpu_mem_usage=True, 
-        **kwargs
-        )
-    
-    tokenizer.add_tokens([DEFAULT_IMAGE_TOKEN], special_tokens=True)
-    model.resize_token_embeddings(len(tokenizer))
-    vision_tower = model.get_vision_tower()
-    vision_tower.to(device=device, dtype=torch.float16)
-    image_processor = vision_tower.image_processor
-
-    if hasattr(model.config, "max_sequence_length"):
-        context_len = model.config.max_sequence_length
-    else:
-        context_len = 2048
-
-    return tokenizer, model, image_processor, context_len
-