Duplicate from riffusion/riffusion-model-v1

Co-authored-by: Seth Forsgren <sethforsgren@users.noreply.huggingface.co>

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+license: creativeml-openrail-m
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- text-to-audio
+inference: true
+extra_gated_prompt: >-
+  This model is open access and available to all, with a CreativeML OpenRAIL-M
+  license further specifying rights and usage.
+
+  The CreativeML OpenRAIL License specifies: 
+
+
+  1. You can't use the model to deliberately produce nor share illegal or
+  harmful outputs or content 
+
+  2. Riffusion claims no rights on the outputs you generate, you are free to use
+  them and are accountable for their use which must not go against the
+  provisions set in the license
+
+  3. You may re-distribute the weights and use the model commercially and/or as
+  a service. If you do, please be aware you have to include the same use
+  restrictions as the ones in the license and share a copy of the CreativeML
+  OpenRAIL-M to all your users (please read the license entirely and carefully)
+
+  Please read the full license carefully here:
+  https://huggingface.co/spaces/CompVis/stable-diffusion-license
+      
+extra_gated_heading: Please read the LICENSE to access this model
+duplicated_from: riffusion/riffusion-model-v1
+---
+
+# Riffusion
+
+Riffusion is an app for real-time music generation with stable diffusion.
+
+Read about it at https://www.riffusion.com/about and try it at https://www.riffusion.com/.
+
+* Web app: https://github.com/hmartiro/riffusion-app
+* Inference server: https://github.com/hmartiro/riffusion-inference
+* Model checkpoint: https://huggingface.co/riffusion/riffusion-model-v1
+
+This repository contains the model files, including:
+
+ * a diffusers formated library
+ * a compiled checkpoint file
+ * a traced unet for improved inference speed
+ * a seed image library for use with riffusion-app
+
+# Riffusion v1 Model
+
+Riffusion is a latent text-to-image diffusion model capable of generating spectrogram images given any text input. These spectrograms can be converted into audio clips.
+
+The model was created by [Seth Forsgren](https://sethforsgren.com/) and [Hayk Martiros](https://haykmartiros.com/) as a hobby project.
+
+You can use the Riffusion model directly, or try the [Riffusion web app](https://www.riffusion.com/).
+
+The Riffusion model was created by fine-tuning the **Stable-Diffusion-v1-5** checkpoint. Read about Stable Diffusion here [🤗's Stable Diffusion blog](https://huggingface.co/blog/stable_diffusion).
+
+## Model Details
+- **Developed by:** Seth Forsgren, Hayk Martiros
+- **Model type:** Diffusion-based text-to-image generation model
+- **Language(s):** English
+- **License:** [The CreativeML OpenRAIL M license](https://huggingface.co/spaces/CompVis/stable-diffusion-license) is an [Open RAIL M license](https://www.licenses.ai/blog/2022/8/18/naming-convention-of-responsible-ai-licenses), adapted from the work that [BigScience](https://bigscience.huggingface.co/) and [the RAIL Initiative](https://www.licenses.ai/) are jointly carrying in the area of responsible AI licensing. See also [the article about the BLOOM Open RAIL license](https://bigscience.huggingface.co/blog/the-bigscience-rail-license) on which our license is based.
+- **Model Description:** This is a model that can be used to generate and modify images based on text prompts. It is a [Latent Diffusion Model](https://arxiv.org/abs/2112.10752) that uses a fixed, pretrained text encoder ([CLIP ViT-L/14](https://arxiv.org/abs/2103.00020)) as suggested in the [Imagen paper](https://arxiv.org/abs/2205.11487).
+
+## Direct Use 
+The model is intended for research purposes only. Possible research areas and
+tasks include
+
+- Generation of artworks, audio, and use in creative processes.
+- Applications in educational or creative tools.
+- Research on generative models.
+
+## Citation
+
+If you build on this work, please cite it as follows:
+
+```
+@software{Forsgren_Martiros_2022,
+  author = {Forsgren, Seth* and Martiros, Hayk*},
+  title = {{Riffusion - Stable diffusion for real-time music generation}},
+  url = {https://riffusion.com/about},
+  year = {2022}
+}
+```

feature_extractor/preprocessor_config.json

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+{
+  "crop_size": 224,
+  "do_center_crop": true,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_resize": true,
+  "feature_extractor_type": "CLIPFeatureExtractor",
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "resample": 3,
+  "size": 224
+}

model_index.json

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+{
+  "_class_name": "StableDiffusionPipeline",
+  "_diffusers_version": "0.4.0",
+  "feature_extractor": [
+    "transformers",
+    "CLIPFeatureExtractor"
+  ],
+  "safety_checker": [
+    "stable_diffusion",
+    "StableDiffusionSafetyChecker"
+  ],
+  "scheduler": [
+    "diffusers",
+    "PNDMScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

riffusion-model-v1.ckpt

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scheduler/scheduler_config.json

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