Testing the reflection idea. With the base vison model.
from llava.model.builder import load_pretrained_model
from llava.mm_utils import get_model_name_from_path, process_images, tokenizer_image_token
from llava.constants import IMAGE_TOKEN_INDEX, DEFAULT_IMAGE_TOKEN, DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN, IGNORE_INDEX
from llava.conversation import conv_templates, SeparatorStyle
from PIL import Image
import requests
import copy
import torch
pretrained = "mylesgoose/Meta-Llama-3.1-8B-Instruct-goose-abliterated-pre-llava-reflection"
model_name = "llava_llama3"
device = "cuda"
device_map = "auto"
tokenizer, model, image_processor, max_length = load_pretrained_model(pretrained, None, model_name, device_map=device_map, attn_implementation="flash_attention_2") # Add any other thing you want to pass in llava_model_args
model.eval()
model.tie_weights()
image = Image.open("/home/myles/Desktop/extreme_ironing.jpg")
image_tensor = process_images([image], image_processor, model.config)
image_tensor = [_image.to(dtype=torch.float16, device=device) for _image in image_tensor]
conv_template = "llava_llama_3"
question = DEFAULT_IMAGE_TOKEN + "\nWhat is shown in this image? Is there anything strange about this image? Is this normal behaviour."
conv = copy.deepcopy(conv_templates[conv_template])
conv.append_message(conv.roles[0], question)
conv.append_message(conv.roles[1], None)
prompt_question = conv.get_prompt()
input_ids = tokenizer_image_token(prompt_question, tokenizer, IMAGE_TOKEN_INDEX, return_tensors="pt").unsqueeze(0).to(device)
image_sizes = [image.size]
cont = model.generate(
input_ids,
images=image_tensor,
image_sizes=image_sizes,
do_sample=True,
temperature=0.7,
max_new_tokens=120000,
)
text_outputs = tokenizer.batch_decode(cont, skip_special_tokens=True)
print(text_outputs)
and template in conversation.py :
conv_llava_llama_3 = Conversation(
system="<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nYou are a helpful language and vision, AI. " "You are able to understand the visual content that the user provides, " "and assist the user with a variety of tasks using natural language, You are a world-class AI system, capable of complex reasoning and reflection. Reason through the query inside tags, and then provide your final response inside
