stable-diffusion-tensorflow
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Stable Diffusion in TensorFlow / Keras
prompt:a bit cat steps: 50 size: 512 * 512 cfg: 7.5 number: 1 pytorch: 36.77s / 1.2~1.4it/s tf: 42.95s / 1.1 ~ 1.4 it/s WHY ?
For some reason, the first generated image is different from the following ones using the code below: ``` from tensorflow import keras from stable_diffusion_tf.stable_diffusion import Text2Image from PIL import Image...
Hi, Requesting for onnx support for the following model weights you have provided here : [https://huggingface.co/fchollet/stable-diffusion/resolve/main/diffusion_model.h5](url) Thanks
Thank you for doing this - I tried a few tutorials to get Stable-Diffusion to work and found this one the best. Similar to : https://github.com/CompVis/stable-diffusion/blob/main/README.md#image-modification-with-stable-diffusion How can I upscale...
This PR allows passing the `--batch` parameter on the command line so that more than one image can be generated at once. By default, this is set to `1` to...
What sampler does this implementation use by default? Is it K_LMS?
In a pipeline I replaced the pytorch version with this implementation, but found the maximum prompt is limited to 77. Is this a compromise for some reasons?
Thanks and congratz for this awesome piece of work. Could you add to the repo whatever script was used to convert the original SD PyTorch checkpoint to the TF weights...
In stable_diffusion.py, ``` if download_weights: text_encoder_weights_fpath = keras.utils.get_file( origin="https://huggingface.co/fchollet/stable-diffusion/resolve/main/text_encoder.h5", file_hash="d7805118aeb156fc1d39e38a9a082b05501e2af8c8fbdc1753c9cb85212d6619", ) diffusion_model_weights_fpath = keras.utils.get_file( origin="https://huggingface.co/fchollet/stable-diffusion/resolve/main/diffusion_model.h5", file_hash="a5b2eea58365b18b40caee689a2e5d00f4c31dbcb4e1d58a9cf1071f55bbbd3a", ) decoder_weights_fpath = keras.utils.get_file( origin="https://huggingface.co/fchollet/stable-diffusion/resolve/main/decoder.h5", file_hash="6d3c5ba91d5cc2b134da881aaa157b2d2adc648e5625560e3ed199561d0e39d5", ) text_encoder.load_weights(text_encoder_weights_fpath) diffusion_model.load_weights(diffusion_model_weights_fpath) decoder.load_weights(decoder_weights_fpath) ``` It seems to...
Can I train custom pretrain data in tensorflow