Share and discover more about AI with social posts from the community.huggingface/OpenAi
It is with great pleasure I inform you that huggingface's ModelHubMixin reached 200+ models on the hub 🥳
ModelHubMixin is a class developed by HF to integrate AI models with the hub with ease and it comes with 3 methods :
* save_pretrained
* from_pretrained
* push_to_hub
Shoutout to @nielsr , @Wauplin and everyone else on HF for their awesome work 🤗
If you are not familiar with ModelHubMixin and you are looking for extra resources you might consider :
* docs: https://huggingface.co/docs/huggingface_hub/main/en/package_reference/mixins
🔗blog about training models with the trainer API and using ModelHubMixin: https://huggingface.co/blog/not-lain/trainer-api-and-mixin-classes
🔗GitHub repo with pip integration: https://github.com/not-lain/PyTorchModelHubMixin-template
🔗basic guide: https://huggingface.co/posts/not-lain/884273241241808
ModelHubMixin is a class developed by HF to integrate AI models with the hub with ease and it comes with 3 methods :
* save_pretrained
* from_pretrained
* push_to_hub
Shoutout to @nielsr , @Wauplin and everyone else on HF for their awesome work 🤗
If you are not familiar with ModelHubMixin and you are looking for extra resources you might consider :
* docs: https://huggingface.co/docs/huggingface_hub/main/en/package_reference/mixins
🔗blog about training models with the trainer API and using ModelHubMixin: https://huggingface.co/blog/not-lain/trainer-api-and-mixin-classes
🔗GitHub repo with pip integration: https://github.com/not-lain/PyTorchModelHubMixin-template
🔗basic guide: https://huggingface.co/posts/not-lain/884273241241808
I have finished writing a blogpost about building an image-based retrieval system, This is one of the first-ever approaches to building such a pipeline using only open-source models/libraries 🤗
You can checkout the blogpost in https://huggingface.co/blog/not-lain/image-retriever and the associated space at
not-lain/image-retriever
.
✨ If you want to request another blog post consider letting me know down below or you can reach out to me through any of my social media
📖 Happy reading !
You can checkout the blogpost in https://huggingface.co/blog/not-lain/image-retriever and the associated space at
not-lain/image-retriever
.
✨ If you want to request another blog post consider letting me know down below or you can reach out to me through any of my social media
📖 Happy reading !
huggingface.co
Image-based search engine
A Blog post by Lain on Hugging Face
AI Comic Factory
Last release: AI Comic Factory 1.2
The AI Comic Factory will soon have an official website: aicomicfactory.app
For more information about my other projects please check linktr.ee/FLNGR.
Running the project at home
First, I would like to highlight that everything is open-source (see here, here, here, here).
However the project isn't a monolithic Space that can be duplicated and ran immediately: it requires various components to run for the frontend, backend, LLM, SDXL etc.
If you try to duplicate the project, open the .env you will see it requires some variables.
Last release: AI Comic Factory 1.2
The AI Comic Factory will soon have an official website: aicomicfactory.app
For more information about my other projects please check linktr.ee/FLNGR.
Running the project at home
First, I would like to highlight that everything is open-source (see here, here, here, here).
However the project isn't a monolithic Space that can be duplicated and ran immediately: it requires various components to run for the frontend, backend, LLM, SDXL etc.
If you try to duplicate the project, open the .env you will see it requires some variables.
distilabel 1.3.0 is out! This release contains many core improvements and new tasks that help us building
argilla/magpie-ultra-v0.1
!
Distributed pipeline execution with Ray, new Magpie tasks, reward models, components for dataset diversity based on sentence embeddings, Argilla 2.0 compatibility and many more features!
Check the new release in GitHub: https://github.com/argilla-io/distilabel
argilla/magpie-ultra-v0.1
!
Distributed pipeline execution with Ray, new Magpie tasks, reward models, components for dataset diversity based on sentence embeddings, Argilla 2.0 compatibility and many more features!
Check the new release in GitHub: https://github.com/argilla-io/distilabel
JoseRFJunior/TransNAR
https://github.com/JoseRFJuniorLLMs/TransNAR
https://arxiv.org/html/2406.09308v1
TransNAR hybrid architecture. Similar to Alayrac et al, we interleave existing Transformer layers with gated cross-attention layers which enable information to flow from the NAR to the Transformer. We generate queries from tokens while we obtain keys and values from nodes and edges of the graph. The node and edge embeddings are obtained by running the NAR on the graph version of the reasoning task to be solved. When experimenting with pre-trained Transformers, we initially close the cross-attention gate, in order to fully preserve the language model’s internal knowledge at the beginning of training.
https://github.com/JoseRFJuniorLLMs/TransNAR
https://arxiv.org/html/2406.09308v1
TransNAR hybrid architecture. Similar to Alayrac et al, we interleave existing Transformer layers with gated cross-attention layers which enable information to flow from the NAR to the Transformer. We generate queries from tokens while we obtain keys and values from nodes and edges of the graph. The node and edge embeddings are obtained by running the NAR on the graph version of the reasoning task to be solved. When experimenting with pre-trained Transformers, we initially close the cross-attention gate, in order to fully preserve the language model’s internal knowledge at the beginning of training.
GitHub
GitHub - JoseRFJuniorLLMs/TransNAR: Transformers and Reasoners Algorítmicos Neurais (NARs)
Transformers and Reasoners Algorítmicos Neurais (NARs) - JoseRFJuniorLLMs/TransNAR
🔥 New state of the art model for background removal is out
🤗 You can try the model at
ZhengPeng7/BiRefNet
📈 model shows impressive results outperforming
briaai/RMBG-1.4
🚀 you can try out the model in:
ZhengPeng7/BiRefNet_demo
📃paper:
Bilateral Reference for High-Resolution Dichotomous Image Segmentation (2401.03407)https://cdn-uploads.huggingface.co/production/uploads/6527e89a8808d80ccff88b7a/lMX02zCeSDvLulbFFuT7N.png
🤗 You can try the model at
ZhengPeng7/BiRefNet
📈 model shows impressive results outperforming
briaai/RMBG-1.4
🚀 you can try out the model in:
ZhengPeng7/BiRefNet_demo
📃paper:
Bilateral Reference for High-Resolution Dichotomous Image Segmentation (2401.03407)https://cdn-uploads.huggingface.co/production/uploads/6527e89a8808d80ccff88b7a/lMX02zCeSDvLulbFFuT7N.png
Live Portrait Updated to V5
Animals Live animation added
All of the main repo changes and improvements added to our modified and improve app
Link : https://patreon.com/posts/107609670
Animals Live animation added
All of the main repo changes and improvements added to our modified and improve app
Link : https://patreon.com/posts/107609670
Patreon
1-Click Installers and Upgraded APP for LivePortrait - Blazing Fast Static Image or Video to Video to Talking and Moving Animation…
Get more from SECourses: Tutorials, Guides, Resources, Training, FLUX, MidJourney, Voice Clone, TTS, ChatGPT, GPT, LLM, Scripts by Furkan Gözü on Patreon
New smol-vision tutorial dropped: QLoRA fine-tuning IDEFICS3-Llama 8B on VQAv2 🐶
Learn how to efficiently fine-tune the latest IDEFICS3-Llama on visual question answering in this notebook 📖
Fine-tuning notebook: https://github.com/merveenoyan/smol-vision/blob/main/Idefics_FT.ipynb
Resulting model:
merve/idefics3llama-vqav2
Learn how to efficiently fine-tune the latest IDEFICS3-Llama on visual question answering in this notebook 📖
Fine-tuning notebook: https://github.com/merveenoyan/smol-vision/blob/main/Idefics_FT.ipynb
Resulting model:
merve/idefics3llama-vqav2
GitHub
smol-vision/Idefics_FT.ipynb at main · merveenoyan/smol-vision
Recipes for shrinking, optimizing, customizing cutting edge vision models. 💜 - merveenoyan/smol-vision