wisconsinaivision / vip-llava Goto Github PK

[CVPR2024] ViP-LLaVA: Making Large Multimodal Models Understand Arbitrary Visual Prompts

License: Apache License 2.0

Dockerfile 0.30% Shell 7.22% Python 88.72% HTML 1.48% JavaScript 1.92% CSS 0.35%

chatbot clip cvpr2024 foundation-models gpt-4 gpt-4-vision llama llama2 llava multi-modal vision-language visual-prompting

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2132660698 tomchen-ctj tiantzhang anil2799 pzzhang saikoumonika sssssshf rayjue

vip-llava's Issues

[Question] Will the code for creating Visual Instruction Tuning dataset be released?

Question

Waiting for Visual Instruction Tuning data, and i wonder if the code for generating this dataset will be released, thanks.

[Question] 请问这个文件怎么找不到了呢？convert_vipbench_for_eval.py

Question

请问这个文件怎么找不到了呢？convert_vipbench_for_eval.py

Training Stage

Question

Very exciting work, how long do “Visual Instruction Tuning“ and “Finetuning on GPT-4V Instruction Data“ take?

[Question] About Data Augmentation

Question

I would like to introduce data augmentation to images (texts too in the near future), but I cannot find transforms.
Where can I introduce data augmentation?
Thanks in advance.

[Usage] pre-requisites for multi-image and multi-prompt generation

Describe the issue

Hi there, thank you for sharing this awesome project.

I have one question about the requried packages for multi-image and multi-prompt generation.
In the following link, it says that the version of the "transformers" library should be newer than 4.35.3.
(https://huggingface.co/llava-hf/vip-llava-7b-hf)

At first I installed all the necessary packages including transformers by following the instructions in a README file. (BTW, with the required versions of packages, I've got the same error discussed in #10 when I followed the steps in https://huggingface.co/llava-hf/vip-llava-7b-hf#using-pipeline )

In order to utilize the multi-image and prompt generation functions, I re-installed the transformers to satisfy the condition (4.36.0). However, when I tried to do an inference, there was a conflict between the transforemers and tokenizer libraries.

Could you share which version of packages you used when testing the multi-image and prompt generation options (transformers, tokenziers, accelerate, bitsandbytes and so on)?

ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
vip-llava 1.1.3 requires tokenizers<0.14,>=0.12.1, but you have tokenizers 0.15.2 which is incompatible.
vip-llava 1.1.3 requires transformers==4.31.0, but you have transformers 4.36.0 which is incompatible.

[Question] Can you provide register-specific instruction data with the help of GPT-4V?

Question

hi, author,
Thank you for your contribution. Could you please provide this dataset?

[Question] Finetune Stage 2 Model

Question

First of all, great work and thank you so much for open-source it! I wonder if the stage 2 model(referred as ViP-LLaVA-Base) has been released anywhere? Maybe mucai/vip-llava-13b-pretrain? I am trying to finetune the stage 2 model using custom GPT instruction data. I am looking at scripts/finetune_stage3.sh and wonder if that's the correct script? But model used in the script is ./checkpoints/vip-llava-$model_size-stage2-ft and I dont really see it anywhere. Thank you!

[Question] On the test set used for inference evaluation

Question

Hi, thanks for your contribution.
Could you please provide the test set link or converted file used in docs/Evaluation.md?

[Question] Warning occurred when """model = LlavaLlamaForCausalLM.from_pretrained(model_path, low_cpu_mem_usage=True, **kwargs)""" in builder.py

Question

When I run bash scripts／finetune_stage3.sh or python predict.py, I faced the warning message. I have downloaded the pretrained weights from the huggingface.
Finetuning and Predicting can be done by ignoring this message. However, when I try to load finetuned weights(checkpoints／vip-llava-7b-stage3-ft), the same message occurs.
Is there any idea to sove this? Or can this message be ignored or not? Thanks in advance.

Warning Message

Some weights of the model checkpoint at ./model_weights were not used when initializing LlavaLlamaForCausalLM: ['model.vision_tower.vision_tower.vision_model.encoder.layers.12.self_attn.q_proj.bias', 'model.vision_tower.vision_tower.vision_model.encoder.layers.20.self_attn.v_proj.bias', 'model.vision_tower.vision_tower.vision_model.encoder.layers.12.layer_norm2.bias', 'model.vision_tower.vision_tower.vision_model.encoder.layers.8.self_attn.k_proj.bias', 'model.vision_tower.vision_tower.vision_model.encoder.layers.0.mlp.fc1.bias', 'model.vision_tower.vision_tower.vision_model.encoder.layers.7.self_attn.q_proj.bias', 'model.vision_tower.vision_tower.vision_model.encoder.layers.10.self_attn.v_proj.bias', 'model.vision_tower.vision_tower.vision_model.encoder.layers.12.mlp.fc2.bias', 'model.vision_tower.vision_tower.vision_model.encoder.layers.18.layer_norm1.weight', 'model.vision_tower.vision_tower.vision_model.encoder.layers.3.self_attn.q_proj.bias', 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- This IS expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing LlavaLlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).

Release of Projector Weights

I want to fine-tune the ViP-LLaVA in my data. According to the instruction, I need to download the projector weight of the first stage, but it is displayed in MODEL_ZOO. Could you please release the projector weight? And I want to confirm the detailed steps for fine-tuning on custom datasets. Do I need to go through the Pretrain (feature alignment) stage from scratch? If not, can you publish the model weights after the Pretrain (feature alignment) stage? Thank you very much!

Looking forward to your reply!

How to use visual prompts with huggingface?

Question

Thank you for the great work! What is the preferred way to feed in visual prompts with the huggingface endpoint?

[Question] When will the Visual Instruction Tuning data be released?

Question

Excellent work, may i ask when will the Visual Instruction Tuning data be released? Thx.

[Discussion] Unable to use the demo

Discussion

Thanks for your work, but the demo is hard to use, especially the module of 'Upload images'. Is there any solution to upload my own images successfully?

[Issue] Tensor mismatch at Runtime

RuntimeError: The expanded size of the tensor (628) must match the existing size (129) at non-singleton dimension 3. Target sizes: [1, 32, 1, 628]. Tensor sizes: [1, 1, 1, 129]

Issue: Upon running the demo colab notebook here, up until yesterday, I was able to get the expected results, but somehow since today the code throws the below mentioned error :

RuntimeError: The expanded size of the tensor (628) must match the existing size (129) at non-singleton dimension 3. Target sizes: [1, 32, 1, 628]. Tensor sizes: [1, 1, 1, 129]

The error gets triggered upon calling the following piece of code :

generate_ids = model.generate(**inputs, max_new_tokens=200)

Could you please have a look and possibly explain what causes the sudden mismatch?
Please note that the example instances used remain unchanged, i.e, the code is trhowing the tensor mismatch error even with the example included in the demo notebook.

[Question] How to get the VIP-Bench?

Question

Hello @mu-cai ,

Thanks for your excellent work. How can we get the VIP-Bench?

Can u provide the subset only for ViP except llava mix original?

So that it can not be easily missleading model using llava original dataset.

Meanwhile, it looks like the images are missing..

    "id": "vcr-52941",
    "image": "vcr1images/lsmdc_3034_IDES_OF_MARCH/[email protected]",
    "meta_dir": "./dataset/vcr1images/lsmdc_3034_IDES_OF_MARCH/[email protected]",
    "class_names": [
        "person",

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