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License: GNU General Public License v3.0
Tag manager and captioner for image datasets
License: GNU General Public License v3.0
Hey, firstly, I deeply appreciate this tool, it's made my workflow so much smoother and I'm grateful you've shared it. On that note, I had a question that I think is similar to #16 but my use case may be more specific or may even already exist, I just can't find it.
I love the ability to filter images by tag(s) on the fly and add new tags to them, I was wondering if it was possible to rename or delete them as well but affecting only the filtered images? If not, is it possible to add something similar? Thank you!
If I changed the advanced settings, is it possible to restore everything to default? I tried deleting everything related to the installation and reinstalling, it didn't help.
Would be nice to be able to transfer tags from one image to another.
A common use case is tagging a set of images that are related to each other. Often many tags are common -- when I'm going down a list of images, I like to use the previous image's captions as a starting point.
Didn't find a way to do this in the gui.
I would love to see support for Qwen-VL- Max added!
It would be very useful if we could create a list of banned tokens to keep it from from using low confidence words like "seems, appears, possibly, suggests" etc.
This feature would be useful, for example when I realize that the prompt could be better and needs to be replaced.
Tried using the auto-captioner feature for the first time. Kept the default settings, and after it downloaded a bunch of models it shows this error in the GUI (nothing in the console). It wont let me copy/paste the whole error from GUI, so I typed the relevant parts here:
Loading THUDM/cogagent-vqa-hf...
A matching Triton is not available, some optimizations will not be enabled
Traceback (most recent call last):
...
... _backends.py line 408, in is_appropriate_type
return isinstance(tensor, (self.tf.Tensor.self.tf.Variable))
AttributeError:
module 'tensorflow' has no attribute 'Tensor'
I have an RTX 3060 12GB, Windows 10.
If I can't get this working, where is the download directory so I can delete the 34GB of models that were downloaded? edit: found the models at: C:\Users\<USER>\.cache\huggingface\hub\models--THUDM--cogagent-vqa-hf
Traceback (most recent call last):
File "run_gui.py", line 24, in
File "run_gui.py", line 18, in run_gui
File "widgets\main_window.py", line 153, in init
File "widgets\main_window.py", line 530, in restore
File "widgets\main_window.py", line 184, in load_directory
File "models\image_list_model.py", line 100, in load_directory
File "pathlib.py", line 1059, in read_text
File "encodings\cp1252.py", line 23, in decode
UnicodeDecodeError: 'charmap' codec can't decode byte 0x9d in position 116: character maps to
Blip captioning sometimes produces characters outside what this app will accept. The larger issue is once a directory that contains caption files that have offending characters has produced this error, you can no longer open the app unless you rename/relocate the offending directory, which is fine, unless you forget which directory you last attempted. Please provide a fix or workaround. Where does the app store the record of last directory attempted?
I would love to see support for Qwen-VL added! The weights for this version are available, see below.
Going though a huge list of images and working on the tags the meaning of arrow keys / cursor up and down is to change the selected tag in the top right window as it has the focus.
To get to the next image I have to click on the left and then I can use the a arrow keys to switch between images again.
I would be great when page up / down would always switch to the next image, that would save me multiple clicks - per image!
Hi, thanks for your great work.
CogVLM doesn't seem to load correctly in 4-bit.
According to CogVLM's README
For INT4 quantization: 1 * RTX 3090(24G) (CogAgent takes ~ 12.6GB, CogVLM takes ~ 11GB)
But when I check “Load in 4-bit” and load CogVLM, it still takes up close to 32GB VRAM.
I think the problem may be here
You can check the code from CogVLM. They load the model in 4-bit like this.
It would be great when I could use wildcards (a *
would be enough, a complete RegEx could be overkill) in the tag filter to filter the images shown
Hello!
I would love to see the 2nd version of moonbeam added to taggui. It’s a smaller model at under 4gb, and has recently been released.
Hi @jhc13, thanks for your contribution. I just wanna ask, how to remove some tags in a large batch and/or for one image?
Thanks.
Hello!
I would love it if we could get an option in the settings menu to enable dark mode. I saw some images on the main repo page with it enabled and it looked great. I’m up late and the regular mode is a bit bright for me.
I'd like to hear if anyone has done a comparative study of best model. As well as the best prompt. Currently my "Write visual tags for the current image, comma-separated" does not always work as intended.
Looks like the latest (1.9.0) Windows binary release does not include bitsandbytes with CUDA on Windows support.
There's no 4-bit checkbox on binary 1.9.0 release and trying to caption using llava-hf/llava-1.5-7b-hf on RTX 4060 Ti 16Gb:
Captioning... (device: cuda:0)
Traceback (most recent call last):
File "widgets\auto_captioner.py", line 435, in run
File "torch\utils\_contextlib.py", line 115, in decorate_context
File "transformers\generation\utils.py", line 1834, in generate
File "transformers\generation\utils.py", line 3592, in beam_sample
File "transformers\generation\utils.py", line 2966, in _temporary_reorder_cache
File "transformers\models\llava\modeling_llava.py", line 528, in _reorder_cache
File "transformers\models\llama\modeling_llama.py", line 1288, in _reorder_cache
File "transformers\models\llama\modeling_llama.py", line 1288, in <genexpr>
torch.cuda
.
OutOfMemoryError
:
CUDA out of memory. Tried to allocate 16.00 MiB. GPU 0 has a total capacty of 16.00 GiB of which 0 bytes is free.
Of the allocated memory 15.04 GiB is allocated by PyTorch, and 169.61 MiB is reserved by PyTorch but unallocated.
If reserved but unallocated memory is large try setting max_split_size_mb to avoid fragmentation.
See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
Got the 4-bit quantization of automatic captioning models to work on Windows by:
So something like this:
git clone https://github.com/jhc13/taggui
cd taggui
python -m venv venv
.\venv\Scripts\Activate.ps1
# pytorch with cuda support
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu121
# scipy first for bitsandbytes from jllllll.github.io
pip install scipy
pip install bitsandbytes --index-url=https://jllllll.github.io/bitsandbytes-windows-webui
# all of requirements.txt except for bitsandbytes, scipy, torch:
pip install accelerate==0.25.0 imagesize==1.4.1 Pillow==10.2.0 pyparsing==3.1.1 PySide6==6.6.1 transformers==4.36.2
Loading BLIP-2 model...
Loading checkpoint shards: 0%| | 0/2 [00:00<?, ?it/s]
Loading checkpoint shards: 50%|##### | 1/2 [00:23<00:23, 23.80s/it]
Loading checkpoint shards: 100%|##########| 2/2 [00:35<00:00, 16.76s/it]
Loading checkpoint shards: 100%|##########| 2/2 [00:35<00:00, 17.82s/it]
You shouldn't move a model when it is dispatched on multiple devices.
Traceback (most recent call last):
File "widgets\blip_2_captioner.py", line 316, in run
File "accelerate\big_modeling.py", line 410, in wrapper
RuntimeError
:
You can't move a model that has some modules offloaded to cpu or disk.
I have selected "CPU" for blip 2 captioning, as my vram is 8GB. My system ram is 44GB so easily capable of handling blip2.
If illegal/unsupported file types are present in folders it will crash autocaptioning. Example:
When the autocaptioner gets to the zip file it will crash.
Might add a filter that only attempts to load file extensions that are expected to work, like .jpg, .bmp, .webp, etc. Or, could use a try/catch when using PIL to load to skip any files that fail to load.
Caption Danbooru like tags for Anime Training
https://huggingface.co/SmilingWolf/wd-v1-4-moat-tagger-v2
https://huggingface.co/SmilingWolf/wd-v1-4-convnext-tagger-v2
https://huggingface.co/SmilingWolf/wd-v1-4-convnextv2-tagger-v2
https://huggingface.co/SmilingWolf/wd-v1-4-convnext-tagger
https://huggingface.co/SmilingWolf/wd-v1-4-vit-tagger-v2
https://huggingface.co/SmilingWolf/wd-v1-4-swinv2-tagger-v2
https://huggingface.co/SmilingWolf/wd-v1-4-vit-tagger
https://huggingface.co/7eu7d7/ML-Danbooru/tree/main
cannot multi select image, no box for start caption with text
dont know what is not allowing me to multi select. I am using shift but do not get multiple selection
also cannot start caption with. no box
Is there a chance that we can:
Please add support for this model. https://github.com/vikhyat/moondream
An extra idea which may be feasible or unfeasible (I do not know) is maybe speculative decoding using a smaller model like this. https://arxiv.org/abs/2310.07177
My experience with speculative decoding in LLMs at least is that it greatly speeds up inference time, and perhaps doing the same thing with like cogvlm as a main model and moondream as a speculative decoding model could speed up captioning of large datasets.
Hello! I found a tiny model that gives some impressive results for its size. It would be awesome if it could be added for users with small GPUs.
Python3.11 introduced a new StrEnum that is not available in 3.10
It is used in taggui, hence python3.10 cannot be used.
Python3.10 is currently the default in quite a few distributions. If it's a small change, this could make it easier to get it to run.
I've made a python3.11 virtualenv that seems to work fine; though i had to make sure libxcb-cursor0 is installed to get x11-backend for Qt to work properly.
The error for this is very unobvious.
Next to this, there might be some gentle fixes that'd make getting it to run on Linux a bit easier:
I would love to see support for ShareGPT4V
this is for users who don't have enough disk space on c drive or already have the model files
To give many images a new identical tag I hold the control key and select image by image and at the end I write the new tag name and accept that it will be applied to these many images.
But when I do a clicking mistake, probably forget to hold down the control key, all my work is lost and I have to do the tedious selection again.
=> feature request: have a specialized undo button that is just resorting the last selection I did
Hello!
Thank you so much for this wonderful app! I would love to see support for the new CogAgent visual language models.
cogagent-vqa-hf
cogagent-chat-hf
I downloaded these myself and tried linking to them in the settings but I get the following error:
Unrecognized processing class in I:\Taggui\_taggui\models\cogagent-vqa-hf. Can't instantiate a processor, a tokenizer, an image processor or a feature extractor for this model. Make sure the repository contains the files of at least one of those processing classes.
Captioned data:
Then on double click to edit, it reverts to single line:
This is very difficult to navigate when editing. I think it would be nice if it worked like the Prompt box, which has word wrap. I find myself wanting to tweak autocaptioned data slightly to correct errors but when the text scrolls it is difficult to navigate, even though I know to use keyboard shortcuts such as ctrl-arrow keys, home, end, etc.
I think carriage returns are generally not used in captions? Shift-enter doesn't seem to behave differently than just "enter" key so I don't think the application supports them in the caption data anyway. I would think word wrapping would not cause issues if it were to behave like the autocaption Prompt input box, like below:
Suggested to clear Search Tags input while Clear Image Filter clicked. Also, clear Search Tags after changing dir
It would be nice to add support for opening folders that contain .webp images. Currently when trying to open one, it doesn't want to open it with no error message. When quitting and reopening the software, it throws an error window and quit the program. When reopening again, the software works again but it asks for a new folder.
On the left is Windows Explorer thumbnail view, on the right is Taggui.
These are images taken with a phone, and the way most phones store is to store directly and then put a tag in EXIF of the correct orientation. Unfortunately by default PIL ignores this and you have to explicitly call a function in PIL ImageOps to transform it.
import PIL.ImageOps as ImageOps
...
image = PIL.Image.open(path_name).convert('RGB')
image = ImageOps.exif_transpose(image)
After updating to df23360
Startup error on Windows using latest requirements.txt (PySide6-6.6.2), working normally using PySide6-6.6.1:
PS C:\Users\user\projects\taggui> .\venv\scripts\activate.ps1
(venv) PS C:\Users\user\projects\taggui> git pull
Already up to date.
(venv) PS C:\Users\user\projects\taggui> pip install --upgrade -r requirements.txt
...
Successfully installed PySide6-6.6.2 PySide6-Addons-6.6.2 PySide6-Essentials-6.6.2 shiboken6-6.6.2
(venv) PS C:\Users\user\projects\taggui> python .\taggui\run_gui.py
Traceback (most recent call last):
File "signature_bootstrap.py", line 77, in bootstrap
File "signature_bootstrap.py", line 93, in find_incarnated_files
File "C:\Users\user\AppData\Local\Programs\Python\Python311\Lib\pathlib.py", line 871, in __new__
self = cls._from_parts(args)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\user\AppData\Local\Programs\Python\Python311\Lib\pathlib.py", line 509, in _from_parts
drv, root, parts = self._parse_args(args)
^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\user\AppData\Local\Programs\Python\Python311\Lib\pathlib.py", line 493, in _parse_args
a = os.fspath(a)
^^^^^^^^^^^^
TypeError: expected str, bytes or os.PathLike object, not NoneType
Fatal Python error: could not initialize part 2
Python runtime state: initialized
Current thread 0x00002d98 (most recent call first):
File "<frozen importlib._bootstrap>", line 241 in _call_with_frames_removed
File "<frozen importlib._bootstrap_external>", line 1233 in create_module
File "<frozen importlib._bootstrap>", line 573 in module_from_spec
File "<frozen importlib._bootstrap>", line 676 in _load_unlocked
File "<frozen importlib._bootstrap>", line 1147 in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 1176 in _find_and_load
File "<frozen importlib._bootstrap>", line 241 in _call_with_frames_removed
File "<frozen importlib._bootstrap>", line 1232 in _handle_fromlist
File "C:\Users\user\projects\taggui\venv\Lib\site-packages\PySide6\__init__.py", line 64 in _setupQtDirectories
File "C:\Users\user\projects\taggui\venv\Lib\site-packages\PySide6\__init__.py", line 124 in <module>
File "<frozen importlib._bootstrap>", line 241 in _call_with_frames_removed
File "<frozen importlib._bootstrap_external>", line 940 in exec_module
File "<frozen importlib._bootstrap>", line 690 in _load_unlocked
File "<frozen importlib._bootstrap>", line 1147 in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 1176 in _find_and_load
File "<frozen importlib._bootstrap>", line 241 in _call_with_frames_removed
File "<frozen importlib._bootstrap>", line 1126 in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 1176 in _find_and_load
File "C:\Users\user\projects\taggui\taggui\run_gui.py", line 4 in <module>
Extension modules: numpy.core._multiarray_umath, numpy.core._multiarray_tests, numpy.linalg._umath_linalg, numpy.fft._pocketfft_internal, numpy.random._common, numpy.random.bit_generator, numpy.random._bounded_integers, numpy.random._mt19937, numpy.random.mtrand, numpy.random._philox, numpy.random._pcg64, numpy.random._sfc64, numpy.random._generator, xxsubtype (total: 14)
(venv) PS C:\Users\user\projects\taggui> pip install --upgrade PySide6==6.6.1
...
Successfully installed PySide6-6.6.1 PySide6-Addons-6.6.1 PySide6-Essentials-6.6.1 shiboken6-6.6.1
(venv) PS C:\Users\user\projects\taggui> python .\taggui\run_gui.py
bin C:\Users\user\projects\taggui\venv\Lib\site-packages\bitsandbytes\libbitsandbytes_cuda121.dll
(venv) PS C:\Users\user\projects\taggui> # No errors with PySide6==6.6.1
Scrolling though a huge list of images I want to repeatedly add the same tag.
E.g. in some pictures the person is wearing glasses in others not.
Right now I'm scrolling through the list and control+click to select all relevant images. Once that list is long enough (please see also #26 ) I create and add the tag.
Then I'm continue with the next images, but to give them the same tag I have to start typing.
A good improvement would be to have a shortcut button that adds the last created (selected?) tag to the images that are selected now
After using taggui for 2000 images, I was facing a issue.
When I want to added tag to the tag list, I am not sure if it is exist or some simular tag is exist or not.
It is pretty hard to check by go throughing a long tag list.
Second, I also suggested to add the ability to choose image preview size in left menu.
Sometime, it is too big and easy to miss some images when scrolling.
Error while downloading from https://cdn-lfs-us-1.huggingface.co/repos/32/e4/32e498ae9fa7fe1cb1ce73f3de0e2f60364ef7d1df059d74473d5c17c1845bde/e29f6ec471ca55789ab14947b527729b9c30313ceb1e7726590b85f9f6406cca?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27model-00001-of-00008.safetensors%3B+filename%3D%22model-00001-of-00008.safetensors%22%3B&Expires=1706583380&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTcwNjU4MzM4MH19LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2RuLWxmcy11cy0xLmh1Z2dpbmdmYWNlLmNvL3JlcG9zLzMyL2U0LzMyZTQ5OGFlOWZhN2ZlMWNiMWNlNzNmM2RlMGUyZjYwMzY0ZWY3ZDFkZjA1OWQ3NDQ3M2Q1YzE3YzE4NDViZGUvZTI5ZjZlYzQ3MWNhNTU3ODlhYjE0OTQ3YjUyNzcyOWI5YzMwMzEzY2ViMWU3NzI2NTkwYjg1ZjlmNjQwNmNjYT9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSoifV19&Signature=L%7E1hl8XxnZ%7EOAHJBbgEChtc02q8KW-bwLSBIDiX3bb1voBOIRpfYFiExyeBVHQi1L3ew7N7g86Ukck8EKySZVxCoscuLSje6iD0yQW498AK6RcWkw-2Cw7du-kBB0AaAIsk3zP2qCYXfqu1bvYjok2CC53PLk9UmiE8i71-SBVqyutnOwg9ypVeuWYfr4iC2Wr6FaqSZLL%7ETPtInFW4dkzEnyDRWHrw-Z4mxwfCG3d%7E%7ETLnpoISiDNB1%7Edku-Um5DNuB2t5auAU8T%7ETyTfuEcchVX%7EYm3n6AtTuGPFYFRHoqe17in3PamMUDds1nduAb1xbVwCOBKdH1g%7EwUBORNBw__&Key-Pair-Id=KCD77M1F0VK2B: HTTPSConnectionPool(host='cdn-lfs-us-1.huggingface.co', port=443): Read timed out.
Trying to resume download...
Traceback (most recent call last):
File "run_gui.py", line 24, in
File "run_gui.py", line 18, in run_gui
File "widgets\main_window.py", line 153, in init
File "widgets\main_window.py", line 530, in restore
File "widgets\main_window.py", line 184, in load_directory
File "models\image_list_model.py", line 100, in load_directory
File "pathlib.py", line 1059, in read_text
File "encodings\cp1252.py", line 23, in decode
UnicodeDecodeError: 'charmap' codec can't decode byte 0x9d in position 321: character maps to
The above happens when using captionr to create blip captions. It appears to be related to characters used in the caption txt files. If I manually edit the caption files to remove certain suspected words or puncuation, taggui will load. Is there a limit to how many files this app can handle? Are there ASCII or nonASCII characters that do not work? I am pulling captions via blip from ViT-L-14/openai
First of all, great job on the UI! Really easy to use and allows for fast tagging as advertised.
Now for my feature requests. It would be great to have the ability to select multiple tags for the filtering, as in, select all the images that have a certain set of tags. It would also be nice to be able to do exclusions based on the tags, that is, show all the images except for the ones with a particular (or several) tag(s).
[Report has been formatted to make it more relevant to TagUI devs/users]
I love your tool and think it is hands-down the best available for captioning. However, I had some issues running Kohya_SS with the generated caption files generated by the software.
Kohya_SS (I learned today) by default uses a format called '.caption', I've never heard of, rather than '.txt'. I wanted you to be aware that for users of the console-run CLI, using caption files with the extension '*.txt' will still train with a 'non-terminal' error that results in trained models having no text encoding. The error is very small and as a result, I failed to notice it for 3 months...
Here's a what it looks like buried in the other console messages after running :
Using DreamBooth method.
prepare images.
found directory [to/dataset/folders]\img\100_traing_data_XL contains 88 image files
No caption file found for 88 images. Training will continue without captions for these images. If class token exists, it will be used. / 88枚の画像にキャプションファイルが見つかりませんでした。これらの画像についてはキャプションなしで学習を 続行します。class tokenが存在する場合はそれを使います。
This is what happens, even with text files for every image. I'm pretty sure this only occurs if you don't use the GUI, but I could be wrong.
For others who also use sd-scripts to train directly from the command line, you just add this to your other arguments.
--caption_extension="txt"
It has hard to find a working set of arguments, so here's mine, if anyone wants something that works with a 12GB 3080. Just be sure to change the model dir, vae dir, training dir, output dir, logging dir AND name it by changing '--output_name="Some_Waifu_XL"' to whatever the name of your model should be.
python.exe sdxl_train_network.py --enable_bucket --min_bucket_reso=256 --max_bucket_reso=2048 --pretrained_model_name_or_path=C:/SD/models/Stable-diffusion/dynavisionXLAllInOneStylized_release0557Bakedvae.safetensors --train_data_dir=C:/Users/[yourusername]/Pictures/Input/train/img --caption_extension="txt" --resolution=1024,1024 --output_dir=C:\\Users\\[yourusername]\\Pictures\\Input\\train\\model --logging_dir=C:\\Users\\[yourusername]\\Pictures\\Input\\train\\log --network_alpha=1 --save_model_as=safetensors --network_alpha="1" --save_model_as=safetensors --network_module=networks.lora --text_encoder_lr=0.0004 --unet_lr=0.0004 --network_dim=8 --output_name="Some_Waifu_XL" --lr_scheduler_num_cycles="1" --cache_text_encoder_outputs --no_half_vae --full_bf16 --learning_rate="0.0004" --lr_scheduler="constant" --train_batch_size="1" --max_train_steps="5100" --save_every_n_epochs="1" --mixed_precision="bf16" --save_precision="bf16" --cache_latents --cache_latents_to_disk --optimizer_type="Adafactor" --optimizer_args scale_parameter=False relative_step=False warmup_init=False --max_data_loader_n_workers="0" --bucket_reso_steps=64 --mem_eff_attn --gradient_checkpointing --xformers --bucket_no_upscale --network_train_unet_only --vae=C:/SD/models/VAE/fixFP16ErrorsSDXLLowerMemoryUse_v10.safetensors
I also get an error, if I don't first delete the NPZ files created by TagUI. I was just wondering if someone could explain how/why these files are created and what purpose they serve.
Keep up the great work!
Hi,
Is it possible to set this arg using the windows version? I see this error sometimes when trying some models
Thanks
It could delete selected tag from all instances but how could I add tag to all instances?
I would love to see support for InternLM-XComposer2-VL added!
Im interested for this UI to use the Blip2 model finally, but im having this issue with the automatic installer. Im using python 3.10.6. Dont know why this happen:
Traceback (most recent call last):
File "run_gui.py", line 6, in
File "", line 1176, in _find_and_load
File "", line 1147, in _find_and_load_unlocked
File "", line 690, in _load_unlocked
File "PyInstaller\loader\pyimod02_importers.py", line 385, in exec_module
File "widgets\main_window.py", line 18, in
File "", line 1176, in _find_and_load
File "", line 1147, in _find_and_load_unlocked
File "", line 690, in _load_unlocked
File "PyInstaller\loader\pyimod02_importers.py", line 385, in exec_module
File "widgets\blip_2_captioner.py", line 6, in
File "", line 1176, in _find_and_load
File "", line 1147, in _find_and_load_unlocked
File "", line 690, in load_unlocked
File "PyInstaller\loader\pyimod02_importers.py", line 385, in exec_module
File "torch_init.py", line 133, in
raise err
OSError: [WinError 126] No se puede encontrar el módulo especificado. Error loading "C:\Users\enriq\Downloads\taggui-v1.2.0-windows\taggui-v1.2.0-windows\taggui\torch\lib\cufftw64_10.dll" or one of its dependencies
Is it possible to use JPEG XL, which is lossless and more modern than PNG.
Probably this helps: https://pypi.org/project/pillow-jxl-plugin/
I am getting this error when installing the requirements.txt file. I am on Windows 10 with Python 3.10.9 and CUDA 11.8.
(venv) C:\Users\r\taggui>pip install -r requirements.txt
Ignoring bitsandbytes: markers 'platform_system != "Windows"' don't match your environment
Collecting bitsandbytes==0.41.2.post2 (from -r requirements.txt (line 11))
Downloading https://github.com/jllllll/bitsandbytes-windows-webui/releases/download/wheels/bitsandbytes-0.41.2.post2-py3-none-win_amd64.whl (152.7 MB)
---------------------------------------- 152.7/152.7 MB 36.4 MB/s eta 0:00:00
Ignoring torch: markers 'platform_system != "Windows"' don't match your environment
ERROR: torch-2.1.2+cu121-cp311-cp311-win_amd64.whl is not a supported wheel on this platform.
(venv) C:\Users\r\taggui>pip install https://download.pytorch.org/whl/cu121/torch-2.1.2%2Bcu121-cp311-cp311-win_amd64.whl
ERROR: torch-2.1.2+cu121-cp311-cp311-win_amd64.whl is not a supported wheel on this platform.```
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.