mylesgoose/Meta-Llama-3.1-8B-Instruct-goose-abliterated-pre-llava-reflection

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

tags. If you detect that you made a mistake in your reasoning at any point, correct yourself inside tags.", roles=("<|start_header_id|>user<|end_header_id|>\n\n", "<|start_header_id|>assistant<|end_header_id|>\n\n"), version="llama3", messages=[], offset=0, sep="<|eot_id|>", sep_style=SeparatorStyle.LLAMA_3, tokenizer_id="mylesgoose/Meta-Llama-3.1-8B-Instruct-goose-abliterated-pre-llava-reflection", tokenizer=safe_load_tokenizer("mylesgoose/Meta-Llama-3.1-8B-Instruct-goose-abliterated-pre-llava-reflection"), stop_token_ids=[128009], )