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alvdansen
/
flux-koda
#StableDiffusion #Flux #AI #ComfyUI
Model description
Koda captures the nostalgic essence of early 1990s photography, evoking memories of disposable cameras and carefree travels. It specializes in creating images with a distinct vintage quality, characterized by slightly washed-out colors, soft focus, and the occasional light leak or film grain. The model excels at producing slice-of-life scenes that feel spontaneous and candid, as if plucked from a family photo album or a backpacker's travel diary.
Words that can highlight interesting nuances within the model:
kodachrome, blurry, realistic, still life, depth of field, scenery, no humans, monochrome, greyscale, traditional media, horizon, looking at viewer, light particles, shadow
https://cdn-uploads.huggingface.co/production/uploads/635dd6cd4fabde0df74aeae6/7CqMzFOlH6yoM-NpQdYDs.png
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flux-koda
#StableDiffusion #Flux #AI #ComfyUI
Model description
Koda captures the nostalgic essence of early 1990s photography, evoking memories of disposable cameras and carefree travels. It specializes in creating images with a distinct vintage quality, characterized by slightly washed-out colors, soft focus, and the occasional light leak or film grain. The model excels at producing slice-of-life scenes that feel spontaneous and candid, as if plucked from a family photo album or a backpacker's travel diary.
Words that can highlight interesting nuances within the model:
kodachrome, blurry, realistic, still life, depth of field, scenery, no humans, monochrome, greyscale, traditional media, horizon, looking at viewer, light particles, shadow
https://cdn-uploads.huggingface.co/production/uploads/635dd6cd4fabde0df74aeae6/7CqMzFOlH6yoM-NpQdYDs.png
ostris / flux-dev-lora-trainer
Train ostris/flux-dev-lora-trainer
Trainings for this model run on Nvidia H100 GPU hardware, which costs $0.001528 per second.
If you haven’t yet trained a model on Replicate, we recommend you read one of the following guides.
Fine-tune an image model
Fine-tune SDXL with your own images
Create training
The easiest way to train ostris/flux-dev-lora-trainer is to use the form below. Upon creation, you will be redirected to the training detail page where you can monitor your training's progress, and eventually download the weights and run the trained model.https://replicate.com/ostris/flux-dev-lora-trainer/train
Train ostris/flux-dev-lora-trainer
Trainings for this model run on Nvidia H100 GPU hardware, which costs $0.001528 per second.
If you haven’t yet trained a model on Replicate, we recommend you read one of the following guides.
Fine-tune an image model
Fine-tune SDXL with your own images
Create training
The easiest way to train ostris/flux-dev-lora-trainer is to use the form below. Upon creation, you will be redirected to the training detail page where you can monitor your training's progress, and eventually download the weights and run the trained model.https://replicate.com/ostris/flux-dev-lora-trainer/train
The flux-lora-collection is a series of LoRA training checkpoints for the FLUX.1-dev model released by the XLabs AI team. This collection supports the generation of images in various styles and themes, such as anthropomorphism, anime, and Disney styles, offering high customizability and innovation.
https://huggingface.co/XLabs-AI/flux-lora-collection
https://huggingface.co/XLabs-AI/flux-lora-collection
🚀 OV-DINO (Open-Vocabulary Detection with Instance-level Noise Optimization)
New approach to open-vocabulary object detection. It improves the ability of vision models to detect and identify objects in images, even objects outside training data.
🤩 SAM2 integration in Demo👇
New approach to open-vocabulary object detection. It improves the ability of vision models to detect and identify objects in images, even objects outside training data.
🤩 SAM2 integration in Demo👇
VGGHeads
- Gradio demo: https://huggingface.co/spaces/okupyn/vgg_heads
- 5 visualization: 'Full', 'Head Boxes', 'Face Landmarks', 'Head Mesh', 'Head Pose'
- Model predicts various aspects of head detection & reconstruction perfectly
- VR, gaming, & animation uses
- 2D image inputs for 3D head outputs
- Gradio demo: https://huggingface.co/spaces/okupyn/vgg_heads
- 5 visualization: 'Full', 'Head Boxes', 'Face Landmarks', 'Head Mesh', 'Head Pose'
- Model predicts various aspects of head detection & reconstruction perfectly
- VR, gaming, & animation uses
- 2D image inputs for 3D head outputs
📣 LLM-DetectAIve: Fine grained detection of machine-generated text
Classifies any text into 4 categories: Human-written, Machine-generated, Machine-written machine-humanized, and Human-written machine-polished💡😀
More nuanced compared to the current binary classification sota
Classifies any text into 4 categories: Human-written, Machine-generated, Machine-written machine-humanized, and Human-written machine-polished💡😀
More nuanced compared to the current binary classification sota
Text-to-Single-ID Generation
🚀🚀🚀Quick start:
1. Enter a text prompt (Chinese or English), Upload an image with a face, and Click the Run button.
2. (Optional) You can also upload an image as the style reference for the results. 🤗
💡💡💡Tips:
1. Try to avoid creating too small faces, as this may lead to some artifacts. (Currently, the short side length of the generated image is limited to 512)
2. It's a good idea to upload multiple reference photos of your face to improve the prompt and ID consistency. Additional references can be uploaded in the "ID supplements".
3. The appropriate values of "Face ID Scale" and "Face Structure Scale" are important for balancing the ID and text alignment. We recommend using "Face ID Scale" (0.5~0.7) and "Face Structure Scale" (0.0~0.4). https://huggingface.co/spaces/Junjie96/UniPortrait
🚀🚀🚀Quick start:
1. Enter a text prompt (Chinese or English), Upload an image with a face, and Click the Run button.
2. (Optional) You can also upload an image as the style reference for the results. 🤗
💡💡💡Tips:
1. Try to avoid creating too small faces, as this may lead to some artifacts. (Currently, the short side length of the generated image is limited to 512)
2. It's a good idea to upload multiple reference photos of your face to improve the prompt and ID consistency. Additional references can be uploaded in the "ID supplements".
3. The appropriate values of "Face ID Scale" and "Face Structure Scale" are important for balancing the ID and text alignment. We recommend using "Face ID Scale" (0.5~0.7) and "Face Structure Scale" (0.0~0.4). https://huggingface.co/spaces/Junjie96/UniPortrait
Introducing FalconMamba 7B: An attention-free 7B model which is pretty strong!
🤯Can process unlimited sequence lengths, outperforms traditional models, and fit on a single 24GB GPU.
Open-source and available on HF🤗. FalconMamba-7b Gradio Demo:https://huggingface.co/spaces/tiiuae/falcon-mamba-playground
🤯Can process unlimited sequence lengths, outperforms traditional models, and fit on a single 24GB GPU.
Open-source and available on HF🤗. FalconMamba-7b Gradio Demo:https://huggingface.co/spaces/tiiuae/falcon-mamba-playground
VGGHeads
🤯 Model performs simultaneous head detections and head meshes reconstruction (for multiple faces!) from a single image in a single step.
Runs on a CPU!🚀 More+Link👇https://pbs.twimg.com/media/GUyFx9WWgAAorFY?format=jpg&name=small
🤯 Model performs simultaneous head detections and head meshes reconstruction (for multiple faces!) from a single image in a single step.
Runs on a CPU!🚀 More+Link👇https://pbs.twimg.com/media/GUyFx9WWgAAorFY?format=jpg&name=small
Demo: https://huggingface.co/spaces/Gradio-Community/Text-guided-Flux-Inpainting
Shout out to
@Gothos03
and
@skalskip92
for enabling and showcasing Inpainting with Flux 🙌
Shout out to
@Gothos03
and
@skalskip92
for enabling and showcasing Inpainting with Flux 🙌
UniPortrait is exclusively released with a Gradio demo on the
@huggingface
Spaces!🤩
Code not released yet. Learn more from their Project page: https://aigcdesigngroup.github.io/UniPortrait-Page/
Access the demo at:https://huggingface.co/spaces/Junjie96/UniPortrait
@huggingface
Spaces!🤩
Code not released yet. Learn more from their Project page: https://aigcdesigngroup.github.io/UniPortrait-Page/
Access the demo at:https://huggingface.co/spaces/Junjie96/UniPortrait
Model on 🤗 Hub: https://huggingface.co/THUDM/LongWriter-glm4-9b
Gradio demo available on the repo locally and linked on the project Readme: https://github.com/THUDM/LongWriter?tab=readme-ov-file#%EF%B8%8F-longwriter-deployment
Clone the repo and launch the gradio demo: python trans_web_demo.py 🤠
Demo releasing soon on 🤗 Spaces, stay tuned!
Gradio demo available on the repo locally and linked on the project Readme: https://github.com/THUDM/LongWriter?tab=readme-ov-file#%EF%B8%8F-longwriter-deployment
Clone the repo and launch the gradio demo: python trans_web_demo.py 🤠
Demo releasing soon on 🤗 Spaces, stay tuned!
We're grateful for our amazing community! Harry C (hoveychen on GitHub) has created "gradio-i18n", a package to easily localize Gradio apps!
This solves real developer needs. Gradio developers, now don't hesitate to take your apps global.
Learn more: https://github.com/gradio-app/gradio/issues/2465#issuecomment-2290969699
This solves real developer needs. Gradio developers, now don't hesitate to take your apps global.
Learn more: https://github.com/gradio-app/gradio/issues/2465#issuecomment-2290969699
Online demos for BiRefNet on
@huggingface
Spaces!
Is this the best background removal model out there? 🤯
MIT licensed. 5.5G GPU memory needed for inference for 1024x1024 images.🤩
BiRefNet
🔥 Gradio Demo 1 with ImageSlider output: https://huggingface.co/spaces/not-lain/background-removal
Gradio demo 2 by the author 🙌
https://huggingface.co/spaces/ZhengPeng7/BiRefNet_demo
@huggingface
Spaces!
Is this the best background removal model out there? 🤯
MIT licensed. 5.5G GPU memory needed for inference for 1024x1024 images.🤩
BiRefNet
🔥 Gradio Demo 1 with ImageSlider output: https://huggingface.co/spaces/not-lain/background-removal
Gradio demo 2 by the author 🙌
https://huggingface.co/spaces/ZhengPeng7/BiRefNet_demo
NEW and Hot: AuraSR Upscaler
- 600M parameter
- Based on GigaGAN paper from Adobe
- GANs are much faster than diffusion upscaling
- Upscaling to 1024px in 1/4th of a second
Model and Demo are up on Huggingface Hub. Great work by Fal AI and Gokay Aydogan, respectively.
🔥 AuraSR is a GAN-based Super-Res upscaler for generated images, a variation of the GigaGAN paper for image-conditioned upscaling.
Demo by @NONDA30: https://huggingface.co/spaces/gokaygokay/AuraSR
🔥 Torch implementation is based on the unofficial lucidrains/gigagan-pytorch repository: https://github.com/lucidrains/gigagan-pytorch?ref=blog.fal.ai
- 600M parameter
- Based on GigaGAN paper from Adobe
- GANs are much faster than diffusion upscaling
- Upscaling to 1024px in 1/4th of a second
Model and Demo are up on Huggingface Hub. Great work by Fal AI and Gokay Aydogan, respectively.
🔥 AuraSR is a GAN-based Super-Res upscaler for generated images, a variation of the GigaGAN paper for image-conditioned upscaling.
Demo by @NONDA30: https://huggingface.co/spaces/gokaygokay/AuraSR
🔥 Torch implementation is based on the unofficial lucidrains/gigagan-pytorch repository: https://github.com/lucidrains/gigagan-pytorch?ref=blog.fal.ai
How to run Yi chat models with an API
Posted November 23, 2023 by @nateraw
The Yi series models are large language models trained from scratch by developers at 01.AI. Today, they’ve released two new models: Yi-6B-Chat and Yi-34B-Chat. These models extend the base models, Yi-6B and Yi-34B, and are fine-tuned for chat completion.
Yi-34B currently holds the state-of-the-art for most benchmarks, beating larger models like Llama-70B..
Posted November 23, 2023 by @nateraw
The Yi series models are large language models trained from scratch by developers at 01.AI. Today, they’ve released two new models: Yi-6B-Chat and Yi-34B-Chat. These models extend the base models, Yi-6B and Yi-34B, and are fine-tuned for chat completion.
Yi-34B currently holds the state-of-the-art for most benchmarks, beating larger models like Llama-70B..
Run Code Llama 70B with an API
Posted January 30, 2024 by @cbh123
Code Llama is a code generation model built on top of Llama 2. It can generate code and natural language about code in many programming languages, including Python, JavaScript, TypeScript, C++, Java, PHP, C#, Bash and more.
Today, Meta announced a more powerful new version of Code Llama with 70 billion parameters. It’s one of the highest performing open models. Meta reports a 67.8 on HumanEval, which beats zero-shot GPT-4.
With Replicate, you can run Code Llama 70B in the cloud with one line of code.
Contents
Contents
Code Llama 70B variants
Run Code Llama 70B with JavaScript
Run Code Llama 70B with Python
Run Code Llama 70B with cURL
Keep up to speed
Code Llama 70B variants
There are three variants of Code Llama 70B. The code snippets in this guide use codellama-70b-instruct, but all three variants are available on Replicate:
Code Llama 70B Base is the foundation model.
Code Llama 70B Python is trained on Python code.
Code Llama 70B Instruct is fine-tuned for understanding natural language instructions.
Posted January 30, 2024 by @cbh123
Code Llama is a code generation model built on top of Llama 2. It can generate code and natural language about code in many programming languages, including Python, JavaScript, TypeScript, C++, Java, PHP, C#, Bash and more.
Today, Meta announced a more powerful new version of Code Llama with 70 billion parameters. It’s one of the highest performing open models. Meta reports a 67.8 on HumanEval, which beats zero-shot GPT-4.
With Replicate, you can run Code Llama 70B in the cloud with one line of code.
Contents
Contents
Code Llama 70B variants
Run Code Llama 70B with JavaScript
Run Code Llama 70B with Python
Run Code Llama 70B with cURL
Keep up to speed
Code Llama 70B variants
There are three variants of Code Llama 70B. The code snippets in this guide use codellama-70b-instruct, but all three variants are available on Replicate:
Code Llama 70B Base is the foundation model.
Code Llama 70B Python is trained on Python code.
Code Llama 70B Instruct is fine-tuned for understanding natural language instructions.
Run Snowflake Arctic with an API
Posted April 23, 2024 by @cbh123
Snowflake Arctic is a new open-source language model from Snowflake. Arctic is on-par or better than both Llama 3 8B and Llama 2 70B on all metrics while using less than half of the training compute budget.
It's massive. At 480B, Arctic is the biggest open-source model to date. As expected from a model from Snowflake, it's good at SQL and other coding tasks, and it has a liberal Apache 2.0 license.
With Replicate, you can run Arctic in the cloud with one line of code.
Posted April 23, 2024 by @cbh123
Snowflake Arctic is a new open-source language model from Snowflake. Arctic is on-par or better than both Llama 3 8B and Llama 2 70B on all metrics while using less than half of the training compute budget.
It's massive. At 480B, Arctic is the biggest open-source model to date. As expected from a model from Snowflake, it's good at SQL and other coding tasks, and it has a liberal Apache 2.0 license.
With Replicate, you can run Arctic in the cloud with one line of code.
Picking an SD3 version
Stability AI have packaged up SD3 Medium in different ways to make sure it can run on as many devices as possible.
SD3 uses three different text encoders. (The text encoder is the part that takes your prompt and puts it into a format the model can understand). One of these new text encoders is really big – meaning it uses a lot of memory. If you’re looking at the SD3 Hugging Face weights, you’ll see four options with different text encoder configurations. You should choose which one to use based on your available VRAM.
sd3_medium_incl_clips_t5xxlfp8.safetensors
This encoder contains the model weights, the two CLIP text encoders and the large T5-XXL model in a compressed fp8 format. We recommend these weights for simplicity and best results.
sd3_medium_incl_clips_t5xxlfp16.safetensors
The same as sd3_medium_incl_clips_t5xxlfp8.safetensors, except the T5 part isn’t compressed as much. By using fp16 instead of fp8, you’ll get a slight improvement in your image quality. This improvement comes at the cost of higher memory usage.
sd3_medium_incl_clips.safetensors
This version does away with the T5 element altogether. It includes the weights with just the two CLIP text encoders. This is a good option if you do not have much VRAM, but your results might be very different from the full version. You might notice that this version doesn’t follow your prompts as closely, and it may also reduce the quality of text in images.
sd3_medium.safetensors
This model is just the base weights without any text encoders. If you use these weights, make sure you’re loading the text encoders separately. Stability AI have provided an example ComfyUI workflow for this.
Stability AI have packaged up SD3 Medium in different ways to make sure it can run on as many devices as possible.
SD3 uses three different text encoders. (The text encoder is the part that takes your prompt and puts it into a format the model can understand). One of these new text encoders is really big – meaning it uses a lot of memory. If you’re looking at the SD3 Hugging Face weights, you’ll see four options with different text encoder configurations. You should choose which one to use based on your available VRAM.
sd3_medium_incl_clips_t5xxlfp8.safetensors
This encoder contains the model weights, the two CLIP text encoders and the large T5-XXL model in a compressed fp8 format. We recommend these weights for simplicity and best results.
sd3_medium_incl_clips_t5xxlfp16.safetensors
The same as sd3_medium_incl_clips_t5xxlfp8.safetensors, except the T5 part isn’t compressed as much. By using fp16 instead of fp8, you’ll get a slight improvement in your image quality. This improvement comes at the cost of higher memory usage.
sd3_medium_incl_clips.safetensors
This version does away with the T5 element altogether. It includes the weights with just the two CLIP text encoders. This is a good option if you do not have much VRAM, but your results might be very different from the full version. You might notice that this version doesn’t follow your prompts as closely, and it may also reduce the quality of text in images.
sd3_medium.safetensors
This model is just the base weights without any text encoders. If you use these weights, make sure you’re loading the text encoders separately. Stability AI have provided an example ComfyUI workflow for this.
How to get the best results from Stable Diffusion 3?
Stability AI recently released the weights for Stable Diffusion 3 Medium, a 2 billion parameter text-to-image model that excels at photorealism, typography, and prompt following.
You can run the official Stable Diffusion 3 model on Replicate, and it is available for commercial use. We have also open-sourced our Diffusers and ComfyUI implementations (read our guide to ComfyUI).
In this blog post we’ll show you how to use Stable Diffusion 3 (SD3) to get the best images, including how to prompt SD3, which is a bit different from previous Stable Diffusion models.
To help you experiment, we’ve created an SD3 explorer model that exposes all of the settings we discuss here.https://d31rfu1d3w8e4q.cloudfront.net/static/blog/get-the-best-from-stable-diffusion-3/explorer-screenshot.png
Stability AI recently released the weights for Stable Diffusion 3 Medium, a 2 billion parameter text-to-image model that excels at photorealism, typography, and prompt following.
You can run the official Stable Diffusion 3 model on Replicate, and it is available for commercial use. We have also open-sourced our Diffusers and ComfyUI implementations (read our guide to ComfyUI).
In this blog post we’ll show you how to use Stable Diffusion 3 (SD3) to get the best images, including how to prompt SD3, which is a bit different from previous Stable Diffusion models.
To help you experiment, we’ve created an SD3 explorer model that exposes all of the settings we discuss here.https://d31rfu1d3w8e4q.cloudfront.net/static/blog/get-the-best-from-stable-diffusion-3/explorer-screenshot.png