Comments (4)
holynski
commented on August 17, 2024
1
My guess is also corrupted download.
Where are you download from? Maybe try download via a browser instead of curl? You can access the file here:
https://huggingface.co/timbrooks/instruct-pix2pix/blob/main/instruct-pix2pix-00-22000.ckpt
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brycedrennan
commented on August 17, 2024
ckpt files are zip files. a partial or corrupted download is a good guess though
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rwkeane
commented on August 17, 2024
Corrupted download was my guess so I tried downloading the model via curl twice and had the same result
I'm wondering if there is something off in the Windows implementation of curl
Would anyone be willing to create a .torrent of the model?
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redcartel243
commented on August 17, 2024
I have been getting errors of all kinds for training the model but when it comes to using the pre-trained model to generate images just make sure all the packages are installed and all the files downloaded by download_checkpoints.sh and download_pretrained_sd.sh are in the right place(alternatively you can download them by yourself by opening them as a text file and following the commands). Also make sure that your version of Conda and torch are compatible
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Related Issues (20)
- Regarding the time and device needed for dataset construction
- About pix2pix access huggingface URL
- "Some weights of the model checkpoint at openai/clip-vit-large-patch14 were not used" HOT 2
- Hi , any update ?
- The edit_cli runs well but edit_app returns nothing. HOT 1
- FeatureReguest/Enhancement/Idea
- NOT the file config.json?
- which version cuda should i choose for this application?
- Cannot Download Checkpoint HOT 2
- finetuning pretrained model using the custom dataset HOT 5
- Learning Rate scheduler
- demo broken
- How to Accelerate Training Data Generation with SDXL-Turbo or LCM?
- Torch version conflict between ip2p and k-diffusion HOT 1
- is the finetuned GPT3 model that generates edit captions from edit instructions openly available?
- Max Resolution
- Prompt to prompt implementation for dataset generation
- metadata.jsonl in the clip-filtered-dataset
- AttributeError: 'AutoencoderKL' object has no attribute 'quantize' HOT 2
- RuntimeError: indices should be either on cpu or on the same device as the indexed tensor (cpu) HOT 3
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