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","raw":"I did the simplest random search strategy, but results can potentially be improved with better-guided search methods. "},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"Supports Gemini 2 Flash & Qwen2.5 as verifiers for \"LLMGrading\" 🤗","raw":"Supports Gemini 2 Flash & Qwen2.5 as verifiers for \"LLMGrading\" 🤗"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"The steps are simple:","raw":"The steps are simple:"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"For each round: ","raw":"For each round: "},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"1> Starting by sampling 2 starting noises with different seeds.","raw":"1> Starting by sampling 2 starting noises with different seeds."},{"type":"new_line","raw":"\n"},{"type":"text","value":"2> Score the generations w.r.t a metric. ","raw":"2> Score the generations w.r.t a metric. "},{"type":"new_line","raw":"\n"},{"type":"text","value":"3> Obtain the best generation from the current round.","raw":"3> Obtain the best generation from the current round."},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"If you have more compute budget, go to the next search round. Scale the noise pool (","raw":"If you have more compute budget, go to the next search round. Scale the noise pool ("},{"type":"inline_code","code":"2 ** search_round","raw":"`2 ** search_round`"},{"type":"text","value":") and repeat 1 - 3.","raw":") and repeat 1 - 3."},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"This constitutes the random search method as done in the paper by Google DeepMind.","raw":"This constitutes the random search method as done in the paper by Google DeepMind."},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"Code, more results, and a bunch of other stuff are in the repository. Check it out here: ","raw":"Code, more results, and a bunch of other stuff are in the repository. Check it out here: "},{"type":"link","href":"https://github.com/sayakpaul/tt-scale-flux/","raw":"https://github.com/sayakpaul/tt-scale-flux/"},{"type":"text","value":" 🤗","raw":" 🤗"}],"rawContent":"Inference-time scaling meets Flux.1-Dev (and others) 🔥\n\nPresenting a simple re-implementation of \"Inference-time scaling diffusion models beyond denoising steps\" by Ma et al.\n\nI did the simplest random search strategy, but results can potentially be improved with better-guided search methods. \n\nSupports Gemini 2 Flash & Qwen2.5 as verifiers for \"LLMGrading\" 🤗\n\nThe steps are simple:\n\nFor each round: \n\n1> Starting by sampling 2 starting noises with different seeds.\n2> Score the generations w.r.t a metric. \n3> Obtain the best generation from the current round.\n\nIf you have more compute budget, go to the next search round. Scale the noise pool (`2 ** search_round`) and repeat 1 - 3.\n\nThis constitutes the random search method as done in the paper by Google DeepMind.\n\nCode, more results, and a bunch of other stuff are in the repository. Check it out here: https://github.com/sayakpaul/tt-scale-flux/ 🤗","author":{"_id":"5f7fbd813e94f16a85448745","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1649681653581-5f7fbd813e94f16a85448745.jpeg","fullname":"Sayak Paul","name":"sayakpaul","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":585,"isFollowing":false},"attachments":[{"type":"image","url":"https://cdn-uploads.huggingface.co/production/uploads/5f7fbd813e94f16a85448745/S4stsmgduEvcF2y7b6w9s.png"}],"mentions":[],"reactions":[{"reaction":"🔥","users":["John6666","dingo-actual","xziayro","victor","prithivMLmods"],"count":5},{"reaction":"❤️","users":["Akseltinfat","burtenshaw","ChaoGong"],"count":3},{"reaction":"🚀","users":["John6666"],"count":1}],"publishedAt":"2025-02-18T01:44:29.000Z","updatedAt":"2025-02-18T01:44:47.139Z","commentators":[],"url":"/posts/sayakpaul/418493639663017","totalUniqueImpressions":3090,"identifiedLanguage":{"language":"en","probability":0.8783260583877563},"numComments":0},{"slug":"119760747385970","content":[{"type":"text","value":"We have been cooking a couple of fine-tuning runs on CogVideoX with finetrainers, smol datasets, and LoRA to generate cool video effects like crushing, dissolving, etc.","raw":"We have been cooking a couple of fine-tuning runs on CogVideoX with finetrainers, smol datasets, and LoRA to generate cool video effects like crushing, dissolving, etc."},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"We are also releasing a LoRA extraction utility from a fully fine-tuned checkpoint. I know that kind of stuff has existed since eternity, but the quality on video models was nothing short of spectacular. Below are some links:","raw":"We are also releasing a LoRA extraction utility from a fully fine-tuned checkpoint. I know that kind of stuff has existed since eternity, but the quality on video models was nothing short of spectacular. Below are some links:"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"* Models and datasets: ","raw":"* Models and datasets: "},{"type":"link","href":"https://huggingface.co/finetrainers","raw":"https://huggingface.co/finetrainers"},{"type":"new_line","raw":"\n"},{"type":"text","value":"* finetrainers: ","raw":"* finetrainers: "},{"type":"link","href":"https://github.com/a-r-r-o-w/finetrainers","raw":"https://github.com/a-r-r-o-w/finetrainers"},{"type":"new_line","raw":"\n"},{"type":"text","value":"* LoRA extraction: ","raw":"* LoRA extraction: "},{"type":"link","href":"https://github.com/huggingface/diffusers/blob/main/scripts/extract_lora_from_model.py","raw":"https://github.com/huggingface/diffusers/blob/main/scripts/extract_lora_from_model.py"}],"rawContent":"We have been cooking a couple of fine-tuning runs on CogVideoX with finetrainers, smol datasets, and LoRA to generate cool video effects like crushing, dissolving, etc.\n\nWe are also releasing a LoRA extraction utility from a fully fine-tuned checkpoint. I know that kind of stuff has existed since eternity, but the quality on video models was nothing short of spectacular. Below are some links:\n\n* Models and datasets: https://huggingface.co/finetrainers\n* finetrainers: https://github.com/a-r-r-o-w/finetrainers\n* LoRA extraction: https://github.com/huggingface/diffusers/blob/main/scripts/extract_lora_from_model.py","author":{"_id":"5f7fbd813e94f16a85448745","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1649681653581-5f7fbd813e94f16a85448745.jpeg","fullname":"Sayak 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Exit code: ?. 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File \"/home/user/.local/lib/python3.10/site-packages/gradio/external.py\", line 340, in from_spaces\n config = json.loads(result.group(1))\nAttributeError: 'NoneType' object has no attribute 'group'\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/user/app/app.py\", line 5, in \n io1 = gr.Interface.load(\n File \"/home/user/.local/lib/python3.10/site-packages/gradio/interface.py\", line 108, in load\n return super().load(name=name, src=src, api_key=api_key, alias=alias)\n File \"/home/user/.local/lib/python3.10/site-packages/gradio/blocks.py\", line 1114, in load\n return external.load_blocks_from_repo(name, src, api_key, alias, **kwargs)\n File \"/home/user/.local/lib/python3.10/site-packages/gradio/external.py\", line 57, in load_blocks_from_repo\n blocks: gradio.Blocks = factory_methods[src](name, api_key, alias, **kwargs)\n File \"/home/user/.local/lib/python3.10/site-packages/gradio/external.py\", line 342, in from_spaces\n raise ValueError(\"Could not load the Space: {}\".format(space_name))\nValueError: Could not load the Space: sayakpaul/raindrop-deraining-maxim\n","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"sayakpaul-maxim-spaces.hf.space","stage":"READY"}]},"title":"Maxim Spaces","isLikedByUser":false},{"author":"sayakpaul","authorData":{"_id":"5f7fbd813e94f16a85448745","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1649681653581-5f7fbd813e94f16a85448745.jpeg","fullname":"Sayak Paul","name":"sayakpaul","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":585},"colorFrom":"red","colorTo":"red","createdAt":"2022-10-18T18:09:39.000Z","emoji":"💻","id":"sayakpaul/lol-enhancement-maxim","lastModified":"2022-11-01T00:53:30.000Z","likes":4,"pinned":false,"private":false,"repoType":"space","runtime":{"stage":"RUNTIME_ERROR","hardware":{"current":null,"requested":"t4-small"},"storage":null,"gcTimeout":3600,"errorMessage":" result_iterator\n yield fs.pop().result()\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/concurrent/futures/_base.py\", line 444, in result\n return self.__get_result()\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/concurrent/futures/_base.py\", line 389, in __get_result\n raise self._exception\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/concurrent/futures/thread.py\", line 57, in run\n result = self.fn(*self.args, **self.kwargs)\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/huggingface_hub/_snapshot_download.py\", line 211, in _inner_hf_hub_download\n return hf_hub_download(\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/huggingface_hub/utils/_validators.py\", line 118, in _inner_fn\n return fn(*args, **kwargs)\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/huggingface_hub/file_download.py\", line 1364, in hf_hub_download\n http_get(\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/huggingface_hub/file_download.py\", line 505, in http_get\n r = _request_wrapper(\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/huggingface_hub/file_download.py\", line 442, in _request_wrapper\n return http_backoff(\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/huggingface_hub/utils/_http.py\", line 212, in http_backoff\n response = session.request(method=method, url=url, **kwargs)\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/requests/sessions.py\", line 589, in request\n resp = self.send(prep, **send_kwargs)\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/requests/sessions.py\", line 703, in send\n r = adapter.send(request, **kwargs)\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/requests/adapters.py\", line 501, in send\n raise ConnectionError(err, request=request)\nrequests.exceptions.ConnectionError: ('Connection aborted.', RemoteDisconnected('Remote end closed connection without response'))\n","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"sayakpaul-lol-enhancement-maxim.hf.space","stage":"READY"}]},"title":"LOL Enhancement MAXIM","isLikedByUser":false},{"author":"sayakpaul","authorData":{"_id":"5f7fbd813e94f16a85448745","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1649681653581-5f7fbd813e94f16a85448745.jpeg","fullname":"Sayak Paul","name":"sayakpaul","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":585},"colorFrom":"green","colorTo":"green","createdAt":"2022-10-20T05:51:46.000Z","emoji":"🥑","id":"sayakpaul/sots-outdoor-dehazing-maxim","lastModified":"2022-10-31T11:21:36.000Z","likes":2,"pinned":false,"private":false,"repoType":"space","runtime":{"stage":"RUNTIME_ERROR","hardware":{"current":null,"requested":"t4-small"},"storage":null,"gcTimeout":36000,"errorMessage":"Launch timed out, space was not healthy after 30 min","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"sayakpaul-sots-outdoor-dehazing-maxim.hf.space","stage":"READY"}]},"title":"Sots Outdoor Dehazing MAXIM","isLikedByUser":false},{"author":"sayakpaul","authorData":{"_id":"5f7fbd813e94f16a85448745","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1649681653581-5f7fbd813e94f16a85448745.jpeg","fullname":"Sayak Paul","name":"sayakpaul","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":585},"colorFrom":"gray","colorTo":"gray","createdAt":"2022-10-27T05:30:11.000Z","emoji":"💻","id":"sayakpaul/fivek-retouching-maxim","lastModified":"2022-10-31T11:21:12.000Z","likes":5,"pinned":false,"private":false,"repoType":"space","runtime":{"stage":"RUNTIME_ERROR","hardware":{"current":null,"requested":"t4-small"},"storage":null,"gcTimeout":3600,"errorMessage":"Traceback (most recent call last):\n File \"app.py\", line 5, in \n import gradio as gr\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/gradio/__init__.py\", line 3, in \n import gradio.components as components\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/gradio/components.py\", line 39, in \n from gradio import media_data, processing_utils, utils\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/gradio/processing_utils.py\", line 20, in \n from gradio import encryptor, utils\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/gradio/utils.py\", line 395, in \n class Request:\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/gradio/utils.py\", line 415, in Request\n client = httpx.AsyncClient()\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/httpx/_client.py\", line 1397, in __init__\n self._transport = self._init_transport(\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/httpx/_client.py\", line 1445, in _init_transport\n return AsyncHTTPTransport(\n File \"/home/user/.pyenv/versions/3.8.9/lib/python3.8/site-packages/httpx/_transports/default.py\", line 275, in __init__\n self._pool = httpcore.AsyncConnectionPool(\nTypeError: __init__() got an unexpected keyword argument 'socket_options'\n","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"sayakpaul-fivek-retouching-maxim.hf.space","stage":"READY"}]},"title":"FiveK Retouching MAXIM","isLikedByUser":false},{"author":"sayakpaul","authorData":{"_id":"5f7fbd813e94f16a85448745","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1649681653581-5f7fbd813e94f16a85448745.jpeg","fullname":"Sayak Paul","name":"sayakpaul","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":585},"colorFrom":"blue","colorTo":"blue","createdAt":"2022-10-27T05:18:31.000Z","emoji":"💻","id":"sayakpaul/raindrop-deraining-maxim","lastModified":"2022-10-31T11:20:06.000Z","likes":3,"pinned":false,"private":false,"repoType":"space","runtime":{"stage":"BUILD_ERROR","hardware":{"current":null,"requested":"t4-small"},"storage":null,"gcTimeout":3600,"errorMessage":"Build failed with exit code: 1","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"sayakpaul-raindrop-deraining-maxim.hf.space","stage":"READY"}]},"title":"RainDrop Deraining MAXIM","isLikedByUser":false},{"author":"sayakpaul","authorData":{"_id":"5f7fbd813e94f16a85448745","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1649681653581-5f7fbd813e94f16a85448745.jpeg","fullname":"Sayak Paul","name":"sayakpaul","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":585},"colorFrom":"blue","colorTo":"blue","createdAt":"2022-10-20T05:43:43.000Z","emoji":"💻","id":"sayakpaul/sots-indoor-dehazing-maxim","lastModified":"2022-10-31T11:19:16.000Z","likes":2,"pinned":false,"private":false,"repoType":"space","runtime":{"stage":"BUILD_ERROR","hardware":{"current":null,"requested":"t4-small"},"storage":null,"gcTimeout":36000,"errorMessage":"Build failed with exit code: 1","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"sayakpaul-sots-indoor-dehazing-maxim.hf.space","stage":"READY"}]},"title":"Sots Indoor Dehazing MAXIM","isLikedByUser":false},{"author":"sayakpaul","authorData":{"_id":"5f7fbd813e94f16a85448745","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1649681653581-5f7fbd813e94f16a85448745.jpeg","fullname":"Sayak 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13.5 TFLOPS

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Sayak Paul

sayakpaul

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https://sayak.dev

• RisingSayak
• sayakpaul

AI & ML interests

Diffusion models, representation learning

Recent Activity

updated a dataset about 7 hours ago

huggingface/diffusers-metadata

updated a model about 19 hours ago

sayakpaul/different-lora-from-civitai

liked a model about 19 hours ago

Remade-AI/Inflate

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Organizations

Posts 21

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3090

Inference-time scaling meets Flux.1-Dev (and others) 🔥

Presenting a simple re-implementation of "Inference-time scaling diffusion models beyond denoising steps" by Ma et al.

I did the simplest random search strategy, but results can potentially be improved with better-guided search methods.

Supports Gemini 2 Flash & Qwen2.5 as verifiers for "LLMGrading" 🤗

The steps are simple:

For each round:

1> Starting by sampling 2 starting noises with different seeds.
2> Score the generations w.r.t a metric.
3> Obtain the best generation from the current round.

If you have more compute budget, go to the next search round. Scale the noise pool (2 ** search_round) and repeat 1 - 3.

This constitutes the random search method as done in the paper by Google DeepMind.

Code, more results, and a bunch of other stuff are in the repository. Check it out here: https://github.com/sayakpaul/tt-scale-flux/ 🤗

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Articles 28

Article

36

Remote VAEs for decoding with HF endpoints 🤗

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Collections 2

Flux tools in NF4

Contains Flux Fill, Canny, and Dev checkpoints in NF4.

• 

  diffusers/FLUX.1-Fill-dev-nf4

  Updated Nov 24, 2024 • 10
• 

  diffusers/FLUX.1-Canny-dev-nf4

  Updated Nov 24, 2024 • 2
• 

  diffusers/FLUX.1-Depth-dev-nf4

  Updated Nov 24, 2024 • 3

Optimizing diffusion models

Provides a list of papers focusing on optimizing T2I diffusion models, targeting fewer timesteps, architecture optimization, and more.

• Progressive Distillation for Fast Sampling of Diffusion Models

  Paper • 2202.00512 • Published Feb 1, 2022 • 1

• On Distillation of Guided Diffusion Models

  Paper • 2210.03142 • Published Oct 6, 2022

• InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation

  Paper • 2309.06380 • Published Sep 12, 2023 • 32

• Consistency Models

  Paper • 2303.01469 • Published Mar 2, 2023 • 8

Papers 13

arxiv:2412.03895

arxiv:2412.01487

arxiv:2408.13467

arxiv:2406.06424

Expand 13 papers

spaces 20

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Running

5

Grade Images with Gemini

🚀

Uses Gemini 2.0 Flash to grade images.

Sleeping

Github Release Notes for Diffusers

🐨

Generate release notes for Hugging Face Diffusers

Paused

2

Q8-LTX-Video-Playground

🧨

Running

17

Demo Docker Gradio

📈

Analyze images and receive labels

Build error

7

Convert Kerascv SD to Diffusers

🧨

Build error

13

Generate Custom Pokemons with Stable Diffusion

🐶

Expand 20 spaces

models 58

Sort:  Recently updated

sayakpaul/different-lora-from-civitai

Updated about 19 hours ago • 1

sayakpaul/trained-lumina2-lora-yarn

Text-to-Image • Updated 22 days ago • 44 • • 3

sayakpaul/dummy-lora-state-dicts

Updated 23 days ago

sayakpaul/vjepa-ckpts

Updated 25 days ago

sayakpaul/omnisana-lr_1e-4-wd_0.0001-cd_0.0-scheduler_constant

Text-to-Image • Updated Jan 22 • 78

sayakpaul/FLUX.1-dev-edit-v0

Text-to-Image • Updated Jan 21 • 287 • 39

sayakpaul/cartoon-control-lr_1e-4-wd_1e-4-gs_10.0-cd_0.1

Text-to-Image • Updated Jan 5 • 35 • 6

sayakpaul/q8-ltx-video

Updated Jan 2 • 60 • 6

sayakpaul/yarn_art_lora_sana

Text-to-Image • Updated Dec 16, 2024 • 3 • 1

sayakpaul/bnb-single-file-checkpoint-from-civitai

Updated Dec 4, 2024 • 118

Expand 58 models

datasets 31

Sort:  Recently updated

sayakpaul/kinetics-cosmos-preprocessed

Updated 7 days ago • 12

sayakpaul/sample-datasets

Viewer • Updated 9 days ago • 6 • 42.5k • 1

sayakpaul/arxiv-new-datasets

Viewer • Updated Jan 30 • 3k • 41

sayakpaul/vae-sd-imagenet-256-latents

Updated Jan 10 • 592k • 2

sayakpaul/OmniEdit-mini

Viewer • Updated Jan 5 • 21.1k • 316 • 1

sayakpaul/video-dataset-disney-organized

Viewer • Updated Nov 29, 2024 • 69 • 591 • 5

sayakpaul/pick-a-pic-v2-unique-prompts

Viewer • Updated Nov 9, 2024 • 59k • 72

sayakpaul/poses-controlnet-dataset

Viewer • Updated Aug 29, 2024 • 496 • 153 • 6

sayakpaul/torchao-diffusers

Updated Aug 28, 2024 • 362

sayakpaul/pickapic_v2_webdataset

Viewer • Updated Apr 4, 2024 • 8.7k • 3.34k

Expand 31 datasets