↓ 8 callersFunctionload_pretrained_model(model_path, model_base, model_name, load_8bit=False, load_4bit=False, device_map="auto", device="cuda", use_f
llava/model/builder.py:29
↓ 7 callersMethodprepare_inputs_labels_for_multimodal(
self, input_ids, position_ids, attention_mask, past_key_values, labels,
images, image_sizes=
llava/model/llava_arch.py:154
↓ 2 callersFunctionbuild_prompt_chatbot(problems, shot_qids, prompt_format, use_caption=False, options=["A", "B", "C", "D", "E"], is_test=False)
scripts/convert_sqa_to_llava_base_prompt.py:221
↓ 2 callersFunctioncreate_one_example(format, question, context, choice, answer, lecture, solution, test_example=True)
scripts/convert_sqa_to_llava_base_prompt.py:106
↓ 2 callersFunctioncreate_one_example_gpt4(format, question, context, choice, answer, lecture, solution, test_example=True)
scripts/convert_sqa_to_llava_base_prompt.py:162
↓ 2 callersMethodprocess_image(self, image, image_process_mode, return_pil=False, image_format='PNG', max_len=1344, min_len=672)
llava/conversation.py:113
↓ 1 callersFunctioncreate_data_loader(questions, image_folder, tokenizer, image_processor, model_config, batch_size=1, num_workers=4)
llava/eval/model_vqa_loader.py:70
↓ 1 callersFunctioncreate_one_example_chatbot(format, question, context, choice, answer, lecture, solution, test_example=True)
scripts/convert_sqa_to_llava_base_prompt.py:41