uyo9ko

Hi @hanoonaR, Thank you so much for your hard work and dedication to releasing this dataset and the automatic annotation pipeline. I was reading through the paper and noticed that...

i add some nn.linear in LlavaLlamaForCausalLM, it leads this error. so i modify this func in train.py `multimodal_keywords = ['mm_projector', 'vision_tower', 'vision_resampler', 'my_linear_layer'],` my problem is sloved. ``` def find_all_linear_names(model):...

> Hi @torrinworx! As the [sd-webui/stable-diffusion-webui#911](https://github.com/sd-webui/stable-diffusion-webui/pull/911) PR suggests, you can make the Stable Diffusion models tile-able by patching the `torch.nn.Conv2d` before loading the pipeline: > > ```python > # add...

Good job! but when i use `torchrun --nproc_per_node 8 example.py`, the sentence `prompt = input(f'User: ')` doesn't work well maybe because of parallelism, do you have a solution for that?

求再发一次 +1

> > For minigpt-v2, I've executed the following code to perform CLI-based inference. , but I would greatly appreciate it if you could provide an official CLI-based inference code for...

> > environment.yaml, > > That's really strange. My version is not strictly consistent with environment.yaml. But I checked my input and everything was fine. I asked the question in...

> I've changed the transformer version, but the output is still the same. It doesn't make sense. > > Would it be convenient for you to provide your complete test...

What I do is just replace the code in demo_v2.py from line 520 to the end with the above code.

change ``` model = AutoPeftModelForCausalLM.from_pretrained( path to the output directory, device_map="auto", trust_remote_code=True ).eval() ``` to ``` model = AutoPeftModelForCausalLM.from_pretrained( path to the output directory, device_map="cuda", trust_remote_code=True ).eval() ```