GRID-6X : Layout for Seamless Image Assembly
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Prithiv Sakthi PRO
prithivMLmods
AI & ML interests
Computer Vision - AI/ML
Recent Activity
updated
a Space
about 1 hour ago
prithivMLmods/FLUX-LoRA-DLC
updated
a collection
about 1 hour ago
Flux LoRA Collections
updated
a collection
about 1 hour ago
Flux LoRA Collections
Articles
Organizations
prithivMLmods's activity
reacted to
elliesleightholm's
post with ๐ค
about 5 hours ago
Post
385
I made a beginners guide to Hugging Face Spaces ๐ค I hope it's useful to some of you :)
YouTube video: https://www.youtube.com/watch?v=xqdTFyRdtjQ
Blog: https://www.marqo.ai/blog/how-to-create-a-hugging-face-space
YouTube video: https://www.youtube.com/watch?v=xqdTFyRdtjQ
Blog: https://www.marqo.ai/blog/how-to-create-a-hugging-face-space
- 6 replies
posted
an
update
1 day ago
Post
1114
๐
Glif App's Remixes feature allows you to slap a logo onto anything, seamlessly integrating the input image (logo) into various contexts. The result is stunning remixes that blend the input logo with generated images (img2img logo mapping) for incredible outcomes.
Check out Any Logo Anywhere remixes on Glif: [Glif Remixes](https://glif.app/glifs/cm3o7dfsd002610z48sz89yih/remixes)
๐The browser extension enables thousands of Glif-based img2img workflows on any image you find online. Experience Glif Remix with WebAI: [Chrome Extension](https://chromewebstore.google.com/detail/glif-remix-the-web-with-a/abfbooehhdjcgmbmcpkcebcmpfnlingo)
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๐คHave fun with the cool stuff !!
@prithivMLmods
Check out Any Logo Anywhere remixes on Glif: [Glif Remixes](https://glif.app/glifs/cm3o7dfsd002610z48sz89yih/remixes)
๐The browser extension enables thousands of Glif-based img2img workflows on any image you find online. Experience Glif Remix with WebAI: [Chrome Extension](https://chromewebstore.google.com/detail/glif-remix-the-web-with-a/abfbooehhdjcgmbmcpkcebcmpfnlingo)
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๐คHave fun with the cool stuff !!
@prithivMLmods
replied to
LukeNeumann's
post
2 days ago
Awesome datasets! Looking forward to seeing them in the big leagues soon.๐ฅ๐
reacted to
fffiloni's
post with ๐ฅ
2 days ago
Post
3260
DimensionX is out for you to try and duplicate ๐ค
โ> fffiloni/DimensionX
Discuss Paper: DimensionX: Create Any 3D and 4D Scenes from a Single Image with Controllable Video Diffusion (2411.04928)
Examples by the amazing William Lamkin @phanes
โ> fffiloni/DimensionX
Discuss Paper: DimensionX: Create Any 3D and 4D Scenes from a Single Image with Controllable Video Diffusion (2411.04928)
Examples by the amazing William Lamkin @phanes
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- 4 replies
reacted to
albertvillanova's
post with โค๏ธ
2 days ago
Post
1048
๐จ How green is your model? ๐ฑ Introducing a new feature in the Comparator tool: Environmental Impact for responsible #LLM research!
๐ open-llm-leaderboard/comparator
Now, you can not only compare models by performance, but also by their environmental footprint!
๐ The Comparator calculates COโ emissions during evaluation and shows key model characteristics: evaluation score, number of parameters, architecture, precision, type... ๐ ๏ธ
Make informed decisions about your model's impact on the planet and join the movement towards greener AI!
๐ open-llm-leaderboard/comparator
Now, you can not only compare models by performance, but also by their environmental footprint!
๐ The Comparator calculates COโ emissions during evaluation and shows key model characteristics: evaluation score, number of parameters, architecture, precision, type... ๐ ๏ธ
Make informed decisions about your model's impact on the planet and join the movement towards greener AI!
reacted to
m-ric's
post with ๐ฅ
2 days ago
Post
1287
Great feature alert: ๐ฌ๐ผ๐ ๐ฐ๐ฎ๐ป ๐ป๐ผ๐ ๐๐๐ฒ ๐ฎ๐ป๐ ๐ฆ๐ฝ๐ฎ๐ฐ๐ฒ ๐ฎ๐ ๐ฎ ๐๐ผ๐ผ๐น ๐ณ๐ผ๐ฟ ๐๐ผ๐๐ฟ ๐๐ฟ๐ฎ๐ป๐๐ณ๐ผ๐ฟ๐บ๐ฒ๐ฟ๐.๐ฎ๐ด๐ฒ๐ป๐! ๐ ๏ธ๐ฅ๐ฅ
This lets you take the coolest spaces, like FLUX.1-dev, and use them in agentic workflows with a few lines of code! ๐งโ๐ป
On the video below, I set up my fake vacation pictures where I'm awesome at surfing (I'm really not) ๐
Head to the doc to learn this magic ๐ https://huggingface.co/docs/transformers/main/en/agents_advanced#import-a-space-as-a-tool-
This lets you take the coolest spaces, like FLUX.1-dev, and use them in agentic workflows with a few lines of code! ๐งโ๐ป
On the video below, I set up my fake vacation pictures where I'm awesome at surfing (I'm really not) ๐
Head to the doc to learn this magic ๐ https://huggingface.co/docs/transformers/main/en/agents_advanced#import-a-space-as-a-tool-
reacted to
rwightman's
post with ๐
2 days ago
Post
1525
New MobileNetV4 weights were uploaded a few days ago -- more ImageNet-12k training at 384x384 for the speedy 'Conv Medium' models.
There are 3 weight variants here for those who like to tinker. On my hold-out eval they are ordered as below, not that different, but the Adopt 180 epochs closer to AdamW 250 than to AdamW 180.
* AdamW for 250 epochs - timm/mobilenetv4_conv_medium.e250_r384_in12k
* Adopt for 180 epochs - timm/mobilenetv4_conv_medium.e180_ad_r384_in12k
* AdamW for 180 epochs - timm/mobilenetv4_conv_medium.e180_r384_in12k
This was by request as a user reported impressive results using the 'Conv Large' ImagNet-12k pretrains as object detection backbones. ImageNet-1k fine-tunes are pending, the weights do behave differently with the 180 vs 250 epochs and the Adopt vs AdamW optimizer.
There are 3 weight variants here for those who like to tinker. On my hold-out eval they are ordered as below, not that different, but the Adopt 180 epochs closer to AdamW 250 than to AdamW 180.
* AdamW for 250 epochs - timm/mobilenetv4_conv_medium.e250_r384_in12k
* Adopt for 180 epochs - timm/mobilenetv4_conv_medium.e180_ad_r384_in12k
* AdamW for 180 epochs - timm/mobilenetv4_conv_medium.e180_r384_in12k
This was by request as a user reported impressive results using the 'Conv Large' ImagNet-12k pretrains as object detection backbones. ImageNet-1k fine-tunes are pending, the weights do behave differently with the 180 vs 250 epochs and the Adopt vs AdamW optimizer.
posted
an
update
3 days ago
Post
2932
The (768 x 1024) mix of MidJourney and Flux's LoRA is nearly identical to the actual visual design. It hasnโt undergone much concept art development for now. In the meantime, try out the impressive visual designs on:
๐ฅMidjourney Flux Mix : prithivMLmods/Midjourney-Flux
๐ฅFlux LoRA Collection: prithivMLmods/flux-lora-collections-66dd5908be2206cfaa8519be
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@prithivMLmods ๐ค
๐ฅMidjourney Flux Mix : prithivMLmods/Midjourney-Flux
๐ฅFlux LoRA Collection: prithivMLmods/flux-lora-collections-66dd5908be2206cfaa8519be
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@prithivMLmods ๐ค
reacted to
Xenova's
post with ๐ฅ
3 days ago
Post
3554
Have you tried out ๐ค Transformers.js v3? Here are the new features:
โก WebGPU support (up to 100x faster than WASM)
๐ข New quantization formats (dtypes)
๐ 120 supported architectures in total
๐ 25 new example projects and templates
๐ค Over 1200 pre-converted models
๐ Node.js (ESM + CJS), Deno, and Bun compatibility
๐ก A new home on GitHub and NPM
Get started with
Learn more in our blog post: https://huggingface.co/blog/transformersjs-v3
โก WebGPU support (up to 100x faster than WASM)
๐ข New quantization formats (dtypes)
๐ 120 supported architectures in total
๐ 25 new example projects and templates
๐ค Over 1200 pre-converted models
๐ Node.js (ESM + CJS), Deno, and Bun compatibility
๐ก A new home on GitHub and NPM
Get started with
npm i @huggingface/transformers.Learn more in our blog post: https://huggingface.co/blog/transformersjs-v3
- 2 replies
reacted to
davidberenstein1957's
post with ๐ค
3 days ago
Post
1803
For anyone who struggles with NER or information extraction with LLM.
We showed an efficient workflow for token classification including zero-shot suggestions and model fine-tuning with Argilla, GliNER, the NuMind NuExtract LLM and SpanMarker. @argilla
Video: https://youtu.be/JvLpaYgNd84?feature=shared
Notebooks and slides included to try it yourself ๐
We showed an efficient workflow for token classification including zero-shot suggestions and model fine-tuning with Argilla, GliNER, the NuMind NuExtract LLM and SpanMarker. @argilla
Video: https://youtu.be/JvLpaYgNd84?feature=shared
Notebooks and slides included to try it yourself ๐
reacted to
reach-vb's
post with ๐ค
3 days ago
Post
3931
What a brilliant week for Open Source AI!
Qwen 2.5 Coder by Alibaba - 0.5B / 1.5B / 3B / 7B / 14B/ 32B (Base + Instruct) Code generation LLMs, with 32B tackling giants like Gemnini 1.5 Pro, Claude Sonnet
Qwen/qwen25-coder-66eaa22e6f99801bf65b0c2f
LLM2CLIP from Microsoft - Leverage LLMs to train ultra-powerful CLIP models! Boosts performance over the previous SOTA by ~17%
microsoft/llm2clip-672323a266173cfa40b32d4c
Athene v2 Chat & Agent by NexusFlow - SoTA general LLM fine-tuned from Qwen 2.5 72B excels at Chat + Function Calling/ JSON/ Agents
Nexusflow/athene-v2-6735b85e505981a794fb02cc
Orca Agent Instruct by Microsoft - 1 million instruct pairs covering text editing, creative writing, coding, reading comprehension, etc - permissively licensed
microsoft/orca-agentinstruct-1M-v1
Ultravox by FixieAI - 70B/ 8B model approaching GPT4o level, pick any LLM, train an adapter with Whisper as Audio Encoder
reach-vb/ultravox-audio-language-model-release-67373b602af0a52b2a88ae71
JanusFlow 1.3 by DeepSeek - Next iteration of their Unified MultiModal LLM Janus with RectifiedFlow
deepseek-ai/JanusFlow-1.3B
Common Corpus by Pleais - 2,003,039,184,047 multilingual, commercially permissive and high quality tokens!
PleIAs/common_corpus
I'm sure I missed a lot, can't wait for the next week!
Put down in comments what I missed! ๐ค
Qwen 2.5 Coder by Alibaba - 0.5B / 1.5B / 3B / 7B / 14B/ 32B (Base + Instruct) Code generation LLMs, with 32B tackling giants like Gemnini 1.5 Pro, Claude Sonnet
Qwen/qwen25-coder-66eaa22e6f99801bf65b0c2f
LLM2CLIP from Microsoft - Leverage LLMs to train ultra-powerful CLIP models! Boosts performance over the previous SOTA by ~17%
microsoft/llm2clip-672323a266173cfa40b32d4c
Athene v2 Chat & Agent by NexusFlow - SoTA general LLM fine-tuned from Qwen 2.5 72B excels at Chat + Function Calling/ JSON/ Agents
Nexusflow/athene-v2-6735b85e505981a794fb02cc
Orca Agent Instruct by Microsoft - 1 million instruct pairs covering text editing, creative writing, coding, reading comprehension, etc - permissively licensed
microsoft/orca-agentinstruct-1M-v1
Ultravox by FixieAI - 70B/ 8B model approaching GPT4o level, pick any LLM, train an adapter with Whisper as Audio Encoder
reach-vb/ultravox-audio-language-model-release-67373b602af0a52b2a88ae71
JanusFlow 1.3 by DeepSeek - Next iteration of their Unified MultiModal LLM Janus with RectifiedFlow
deepseek-ai/JanusFlow-1.3B
Common Corpus by Pleais - 2,003,039,184,047 multilingual, commercially permissive and high quality tokens!
PleIAs/common_corpus
I'm sure I missed a lot, can't wait for the next week!
Put down in comments what I missed! ๐ค
reacted to
merve's
post with ๐ค
4 days ago
Post
4654
OmniVision-968M: a new local VLM for edge devices, fast & small but performant
๐จ a new vision language model with 9x less image tokens, super efficient
๐ aligned with DPO for reducing hallucinations
โก๏ธ Apache 2.0 license ๐ฅ
Demo hf.co/spaces/NexaAIDev/omnivlm-dpo-demo
Model NexaAIDev/omnivision-968M
๐จ a new vision language model with 9x less image tokens, super efficient
๐ aligned with DPO for reducing hallucinations
โก๏ธ Apache 2.0 license ๐ฅ
Demo hf.co/spaces/NexaAIDev/omnivlm-dpo-demo
Model NexaAIDev/omnivision-968M
- 4 replies
replied to
their
post
4 days ago
@Csplk
Thank you, It means a lot to hear that. I'm always happy to bring values.
Happy Weekend !
Regards
posted
an
update
4 days ago
Post
3834
Minimalistic Adapters ๐
๐Demo Here:
prithivMLmods/FLUX-LoRA-DLC
๐Model:
{ Quote Tuner } : prithivMLmods/Flux.1-Dev-Quote-LoRA
{ Stamp Art } : prithivMLmods/Flux.1-Dev-Stamp-Art-LoRA
{ Hand Sticky } : prithivMLmods/Flux.1-Dev-Hand-Sticky-LoRA
{ Poster HQ } : prithivMLmods/Flux.1-Dev-Poster-HQ-LoRA
{ Ctoon Min } : prithivMLmods/Flux.1-Dev-Ctoon-LoRA
๐Collection:
{ Flux LoRA Collection} : prithivMLmods/flux-lora-collections-66dd5908be2206cfaa8519be
{ LoRA Space Collection } : prithivMLmods/lora-space-collections-6714b72e0d49e1c97fbd6a32
๐For More Visit
https://huggingface.co/strangerzonehf
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๐ค@prithivMLmods
๐Demo Here:
prithivMLmods/FLUX-LoRA-DLC
๐Model:
{ Quote Tuner } : prithivMLmods/Flux.1-Dev-Quote-LoRA
{ Stamp Art } : prithivMLmods/Flux.1-Dev-Stamp-Art-LoRA
{ Hand Sticky } : prithivMLmods/Flux.1-Dev-Hand-Sticky-LoRA
{ Poster HQ } : prithivMLmods/Flux.1-Dev-Poster-HQ-LoRA
{ Ctoon Min } : prithivMLmods/Flux.1-Dev-Ctoon-LoRA
๐Collection:
{ Flux LoRA Collection} : prithivMLmods/flux-lora-collections-66dd5908be2206cfaa8519be
{ LoRA Space Collection } : prithivMLmods/lora-space-collections-6714b72e0d49e1c97fbd6a32
๐For More Visit
https://huggingface.co/strangerzonehf
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๐ค@prithivMLmods
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- 3 replies
reacted to
MonsterMMORPG's
post with ๐ค
4 days ago
Post
2316
Kohya brought massive improvements to FLUX LoRA (as low as 4 GB GPUs) and DreamBooth / Fine-Tuning (as low as 6 GB GPUs) training - check attached images in full size to see full details
You can download all configs and full instructions
> https://www.patreon.com/posts/112099700 - Fine Tuning post
> https://www.patreon.com/posts/110879657 - LoRA post
Kohya brought massive improvements to FLUX LoRA and DreamBooth / Fine-Tuning (min 6GB GPU) training.
Now as low as 4GB GPUs can train FLUX LoRA with decent quality and 24GB and below GPUs got a huge speed boost when doing Full DreamBooth / Fine-Tuning training
You need minimum 4GB GPU to do a FLUX LoRA training and minimum 6 GB GPU to do FLUX DreamBooth / Full Fine-Tuning training. It is just mind blowing.
You can download all configs and full instructions > https://www.patreon.com/posts/112099700
The above post also has 1-click installers and downloaders for Windows, RunPod and Massed Compute
The model downloader scripts also updated and downloading 30+GB models takes total 1 minute on Massed Compute
You can read the recent updates here : https://github.com/kohya-ss/sd-scripts/tree/sd3?tab=readme-ov-file#recent-updates
This is the Kohya GUI branch : https://github.com/bmaltais/kohya_ss/tree/sd3-flux.1
Key thing to reduce VRAM usage is using block swap
Kohya implemented the logic of OneTrainer to improve block swapping speed significantly and now it is supported for LoRAs as well
Now you can do FP16 training with LoRAs on 24 GB and below GPUs
Now you can train a FLUX LoRA on a 4 GB GPU - key is FP8, block swap and using certain layers training (remember single layer LoRA training)
It took me more than 1 day to test all newer configs, their VRAM demands, their relative step speeds and prepare the configs :)
You can download all configs and full instructions
> https://www.patreon.com/posts/112099700 - Fine Tuning post
> https://www.patreon.com/posts/110879657 - LoRA post
Kohya brought massive improvements to FLUX LoRA and DreamBooth / Fine-Tuning (min 6GB GPU) training.
Now as low as 4GB GPUs can train FLUX LoRA with decent quality and 24GB and below GPUs got a huge speed boost when doing Full DreamBooth / Fine-Tuning training
You need minimum 4GB GPU to do a FLUX LoRA training and minimum 6 GB GPU to do FLUX DreamBooth / Full Fine-Tuning training. It is just mind blowing.
You can download all configs and full instructions > https://www.patreon.com/posts/112099700
The above post also has 1-click installers and downloaders for Windows, RunPod and Massed Compute
The model downloader scripts also updated and downloading 30+GB models takes total 1 minute on Massed Compute
You can read the recent updates here : https://github.com/kohya-ss/sd-scripts/tree/sd3?tab=readme-ov-file#recent-updates
This is the Kohya GUI branch : https://github.com/bmaltais/kohya_ss/tree/sd3-flux.1
Key thing to reduce VRAM usage is using block swap
Kohya implemented the logic of OneTrainer to improve block swapping speed significantly and now it is supported for LoRAs as well
Now you can do FP16 training with LoRAs on 24 GB and below GPUs
Now you can train a FLUX LoRA on a 4 GB GPU - key is FP8, block swap and using certain layers training (remember single layer LoRA training)
It took me more than 1 day to test all newer configs, their VRAM demands, their relative step speeds and prepare the configs :)
reacted to
pagezyhf's
post with ๐
5 days ago
Post
1327
Hello Hugging Face Community,
I'd like to share here a bit more about our Deep Learning Containers (DLCs) we built with Google Cloud, to transform the way you build AI with open models on this platform!
With pre-configured, optimized environments for PyTorch Training (GPU) and Inference (CPU/GPU), Text Generation Inference (GPU), and Text Embeddings Inference (CPU/GPU), the Hugging Face DLCs offer:
โก Optimized performance on Google Cloud's infrastructure, with TGI, TEI, and PyTorch acceleration.
๐ ๏ธ Hassle-free environment setup, no more dependency issues.
๐ Seamless updates to the latest stable versions.
๐ผ Streamlined workflow, reducing dev and maintenance overheads.
๐ Robust security features of Google Cloud.
โ๏ธ Fine-tuned for optimal performance, integrated with GKE and Vertex AI.
๐ฆ Community examples for easy experimentation and implementation.
๐ TPU support for PyTorch Training/Inference and Text Generation Inference is coming soon!
Find the documentation at https://huggingface.co/docs/google-cloud/en/index
If you need support, open a conversation on the forum: https://discuss.huggingface.co/c/google-cloud/69
I'd like to share here a bit more about our Deep Learning Containers (DLCs) we built with Google Cloud, to transform the way you build AI with open models on this platform!
With pre-configured, optimized environments for PyTorch Training (GPU) and Inference (CPU/GPU), Text Generation Inference (GPU), and Text Embeddings Inference (CPU/GPU), the Hugging Face DLCs offer:
โก Optimized performance on Google Cloud's infrastructure, with TGI, TEI, and PyTorch acceleration.
๐ ๏ธ Hassle-free environment setup, no more dependency issues.
๐ Seamless updates to the latest stable versions.
๐ผ Streamlined workflow, reducing dev and maintenance overheads.
๐ Robust security features of Google Cloud.
โ๏ธ Fine-tuned for optimal performance, integrated with GKE and Vertex AI.
๐ฆ Community examples for easy experimentation and implementation.
๐ TPU support for PyTorch Training/Inference and Text Generation Inference is coming soon!
Find the documentation at https://huggingface.co/docs/google-cloud/en/index
If you need support, open a conversation on the forum: https://discuss.huggingface.co/c/google-cloud/69
reacted to
LukeNeumann's
post with ๐ฅ
5 days ago
Post
1829
Hello Hugging Face community!
I wanted to introduce myself and my company @Overlaiapp . We are a collective of filmmakers, photographers, and AI engineers working on high resolution (8K+) training data.
We plan to share a lot of our datasets with the community and are kicking things off with two curated datasets:
- Overlaiai/OregonCoastin4K
- Overlaiai/SubArcticPolarBear
Overlai.ai Dataset Features
๐ฅ Oversampled: Every clip is captured in stunning 8K resolution, delivering rich detail ideal for fine tuning scenic landscapes and ocean dynamics.
๐ธ Variance: Includes close-up details, slow-motion footage of crashing waves, sweeping landscapes, and wildlife shots.
๐ Detailed Metadata: Every clip is paired with structured metadata, including creative descriptions, precise camera movements, lens information, field of view calculations, and shot settings, ensuring AI models can fully understand and replicate real-world cinematography with accuracy.
โ๏ธ Consistency: Re-thinking training data at the point of capture by "overshooting" a subject, enabling models to learn more nuanced relationships and views across scenes.
๐ Light: Shot during early morning and sunset light for optimal color contrast and dynamic range, maximizing visual quality for color and lighting-sensitive tasks.
๐ Curation: Curated specifically for machine learning, providing clean, high-quality data for next generation model training.
I wanted to introduce myself and my company @Overlaiapp . We are a collective of filmmakers, photographers, and AI engineers working on high resolution (8K+) training data.
We plan to share a lot of our datasets with the community and are kicking things off with two curated datasets:
- Overlaiai/OregonCoastin4K
- Overlaiai/SubArcticPolarBear
Overlai.ai Dataset Features
๐ฅ Oversampled: Every clip is captured in stunning 8K resolution, delivering rich detail ideal for fine tuning scenic landscapes and ocean dynamics.
๐ธ Variance: Includes close-up details, slow-motion footage of crashing waves, sweeping landscapes, and wildlife shots.
๐ Detailed Metadata: Every clip is paired with structured metadata, including creative descriptions, precise camera movements, lens information, field of view calculations, and shot settings, ensuring AI models can fully understand and replicate real-world cinematography with accuracy.
โ๏ธ Consistency: Re-thinking training data at the point of capture by "overshooting" a subject, enabling models to learn more nuanced relationships and views across scenes.
๐ Light: Shot during early morning and sunset light for optimal color contrast and dynamic range, maximizing visual quality for color and lighting-sensitive tasks.
๐ Curation: Curated specifically for machine learning, providing clean, high-quality data for next generation model training.
posted
an
update
6 days ago
Post
1620
Animaker / Anime Engine : ๐ค
Only on๐: https://huggingface.co/strangerzonehf
Demo: prithivMLmods/FLUX-LoRA-DLC
Adapters:
->Model 1: strangerzonehf/Flux-Animeo-v1-LoRA
->Model 2: strangerzonehf/Flux-Animex-v2-LoRA
Collections:
->Flux LoRA Collection: prithivMLmods/flux-lora-collections-66dd5908be2206cfaa8519be
->Stranger Zones: prithivMLmods/stranger-zone-collections-6737118adcf2cb40d66d0c7e
->LoRA Spaces: prithivMLmods/lora-space-collections-6714b72e0d49e1c97fbd6a32
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@prithivMLmods
Only on๐: https://huggingface.co/strangerzonehf
Demo: prithivMLmods/FLUX-LoRA-DLC
Adapters:
->Model 1: strangerzonehf/Flux-Animeo-v1-LoRA
->Model 2: strangerzonehf/Flux-Animex-v2-LoRA
Collections:
->Flux LoRA Collection: prithivMLmods/flux-lora-collections-66dd5908be2206cfaa8519be
->Stranger Zones: prithivMLmods/stranger-zone-collections-6737118adcf2cb40d66d0c7e
->LoRA Spaces: prithivMLmods/lora-space-collections-6714b72e0d49e1c97fbd6a32
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@prithivMLmods
- 1 reply
reacted to
AdinaY's
post with ๐ฅ
6 days ago
Post
2479
Letโs dive into the exciting releases from the Chinese community last week ๐ฅ๐
More details ๐ https://huggingface.co/zh-ai-community
Code model:
โจQwen 2.5 coder by Alibaba Qwen
Qwen/qwen25-coder-66eaa22e6f99801bf65b0c2f
โจOpenCoder by InflyAI - Fully open code model๐
infly/opencoder-672cec44bbb86c39910fb55e
Image model:
โจHunyuan3D-1.0 by Tencent
tencent/Hunyuan3D-1
MLLM:
โจJanusFlow by DeepSeek
deepseek-ai/JanusFlow-1.3B
deepseek-ai/JanusFlow-1.3B
โจMono-InternVL-2B by OpenGVlab
OpenGVLab/Mono-InternVL-2B
Video model:
โจCogVideoX 1.5 by ChatGLM
THUDM/CogVideoX1.5-5B-SAT
Audio model:
โจFish Agent by FishAudio
fishaudio/fish-agent-v0.1-3b
Dataset:
โจOPI dataset by BAAIBeijing
BAAI/OPI
More details ๐ https://huggingface.co/zh-ai-community
Code model:
โจQwen 2.5 coder by Alibaba Qwen
Qwen/qwen25-coder-66eaa22e6f99801bf65b0c2f
โจOpenCoder by InflyAI - Fully open code model๐
infly/opencoder-672cec44bbb86c39910fb55e
Image model:
โจHunyuan3D-1.0 by Tencent
tencent/Hunyuan3D-1
MLLM:
โจJanusFlow by DeepSeek
deepseek-ai/JanusFlow-1.3B
deepseek-ai/JanusFlow-1.3B
โจMono-InternVL-2B by OpenGVlab
OpenGVLab/Mono-InternVL-2B
Video model:
โจCogVideoX 1.5 by ChatGLM
THUDM/CogVideoX1.5-5B-SAT
Audio model:
โจFish Agent by FishAudio
fishaudio/fish-agent-v0.1-3b
Dataset:
โจOPI dataset by BAAIBeijing
BAAI/OPI
reacted to
merve's
post with ๐ค
7 days ago
Post
1625
Microsoft released LLM2CLIP: a CLIP model with longer context window for complex text inputs ๐คฏ
All models with Apache 2.0 license here microsoft/llm2clip-672323a266173cfa40b32d4c
TLDR; they replaced CLIP's text encoder with various LLMs fine-tuned on captioning, better top-k accuracy on retrieval.
This will enable better image-text retrieval, better zero-shot image classification, better vision language models ๐ฅ
Read the paper to learn more: LLM2CLIP: Powerful Language Model Unlock Richer Visual Representation (2411.04997)
All models with Apache 2.0 license here microsoft/llm2clip-672323a266173cfa40b32d4c
TLDR; they replaced CLIP's text encoder with various LLMs fine-tuned on captioning, better top-k accuracy on retrieval.
This will enable better image-text retrieval, better zero-shot image classification, better vision language models ๐ฅ
Read the paper to learn more: LLM2CLIP: Powerful Language Model Unlock Richer Visual Representation (2411.04997)