Comments (6)
I also tried !python /content/Text-To-Video-Finetuning/inference.py --model /content/Text-To-Video-Finetuning/models/model_scope_diffusers --prompt "cat in a space suit"
and had the same output
from text-to-video-finetuning.
Hey there. After training, are you pointing to the trained model?
By default, it should be placed at the script root under ./outputs/train_<date>
from text-to-video-finetuning.
What are you trying to view the video in? I’ve found there’s something weird about the codec sometimes and it needs to be viewed in an application like VLC
from text-to-video-finetuning.
Hey there. After training, are you pointing to the trained model?
By default, it should be placed at the script root under ./outputs/train_<date>
Yes I did try the trained model. Trained two different ones in fact.
And then I thought I would do a sanity check and try to generate an image with the installed "base" model and filed this report.
Am I trying to generate an image correctly immediately after install with this line? !python /content/Text-To-Video-Finetuning/inference.py --model /content/Text-To-Video-Finetuning/models/model_scope_diffusers --prompt "cat in a space suit"
because if that command is incorrect I've been on the wrong track.
from text-to-video-finetuning.
If you have lots of videos you might need to train it for longer. How many steps did you train it and how many videos? 2500 is not enough if you are doing hundreds of videos with different prompts each.
from text-to-video-finetuning.
If you have lots of videos you might need to train it for longer. How many steps did you train it and how many videos? 2500 is not enough if you are doing hundreds of videos with different prompts each.
I was using images actually to train the model and there were about a dozen of them. I went the opposite way.
But, the problem as I see it is that one should be able to generate a clip with the inference model before running a training session. I ran into issues with that as well, hence this (possibly errant) bug report.
from text-to-video-finetuning.
Related Issues (20)
- webui Lora Might be causing errors in checkpoint models. HOT 3
- How to train with folder video HOT 1
- Which paper? HOT 1
- RuntimeError: cannot reshape tensor of 0 elements into shape [0, -1, 1, 512] because the unspecified dimension size -1 can be any value and is ambiguous HOT 3
- Does this code support native finetune for damo text to video model? HOT 2
- AttributeError: 'Tensor' object has no attribute 'config' HOT 5
- How can I run the fine-tuning on a GPU with <= 16GB of VRAM? HOT 3
- I have some doubts about the framework HOT 4
- A typo
- TypeError: Linear.forward() got an unexpected keyword argument 'scale' HOT 6
- wrong norm method HOT 1
- issues on train.py HOT 1
- [inference] latents_window index error HOT 1
- Two forward passes in finetune_unet HOT 1
- Lora on ResnetBlock2D in modelscope model HOT 1
- Can the videocomposer model be adapted to this training framework?
- Normal finetuning instead of LoRA
- ControlNet
- init_video problem
- finetune train error of "UnboundLocalError: local variable 'use_offset_noise' referenced before assignment" HOT 2
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