Findora/hf_fr_dioula_full
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Mory KEITA
MonsieurMory
AI & ML interests
I'm an industrial management engineering student and AI enthusiast.
I'm interested about everything related to AI, machine learning and NLP
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Findora/hf_fr_dioula_full
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reacted to
lysandre's
post with ❤️❤️
11 months ago
Post
8297
SmolVLM-2 and SigLIP-2 are now part of
They're added on top of the v4.49.0 release, and can be installed from the following tags:
This marks a new beginning for the release process of transformers. For the past five years, we've been doing monthly releases featuring many models (v4.49.0, the latest release, features 9 new architectures).
Starting with SmolVLM-2 & SigLIP2, we'll now additionally release tags supporting new models on a stable branch. These models are therefore directly available for use by installing from the tag itself. These tags will continue to be updated with fixes applied to these models.
Going forward, continue expecting software releases following semantic versioning: v4.50.0 will have ~10 new architectures compared to v4.49.0, as well as a myriad of new features, improvements and bug fixes. Accompanying these software releases, we'll release tags offering brand new models as fast as possible, to make them accessible to all immediately.
transformers in dedicated releases!They're added on top of the v4.49.0 release, and can be installed from the following tags:
v4.49.0-SmolVLM-2 and v4.49.0-SigLIP-2.This marks a new beginning for the release process of transformers. For the past five years, we've been doing monthly releases featuring many models (v4.49.0, the latest release, features 9 new architectures).
Starting with SmolVLM-2 & SigLIP2, we'll now additionally release tags supporting new models on a stable branch. These models are therefore directly available for use by installing from the tag itself. These tags will continue to be updated with fixes applied to these models.
Going forward, continue expecting software releases following semantic versioning: v4.50.0 will have ~10 new architectures compared to v4.49.0, as well as a myriad of new features, improvements and bug fixes. Accompanying these software releases, we'll release tags offering brand new models as fast as possible, to make them accessible to all immediately.
- 1 reply
liked
a
model
12 months ago
reacted to
sagar007's
post with ❤️❤️
about 1 year ago
Post
3745
🚀 Just built a Perplexity-inspired AI search assistant using Gradio, DeepSeek, and DuckDuckGo!
Ask it anything, and it’ll:
Scour the web for answers 📚
Cite sources like a pro 🔗
Even talk back with TTS (thanks, Kokoro!) 🎙️
Ask it anything, and it’ll:
Scour the web for answers 📚
Check it out → sagar007/DeepSeekR1_Search
Ask it anything, and it’ll:
Scour the web for answers 📚
Cite sources like a pro 🔗
Even talk back with TTS (thanks, Kokoro!) 🎙️
Ask it anything, and it’ll:
Scour the web for answers 📚
Check it out → sagar007/DeepSeekR1_Search
reacted to
prithivMLmods's
post with 🚀
about 1 year ago
Post
6044
Reasoning SmolLM2 🚀
🎯Fine-tuning SmolLM2 on a lightweight synthetic reasoning dataset for reasoning-specific tasks. Future updates will focus on lightweight, blazing-fast reasoning models. Until then, check out the blog for fine-tuning details.
🔥Blog : https://huggingface.co/blog/prithivMLmods/smollm2-ft
🔼 Models :
+ SmolLM2-CoT-360M : prithivMLmods/SmolLM2-CoT-360M
+ Reasoning-SmolLM2-135M : prithivMLmods/Reasoning-SmolLM2-135M
+ SmolLM2-CoT-360M-GGUF : prithivMLmods/SmolLM2-CoT-360M-GGUF
🤠 Other Details :
+ Demo : prithivMLmods/SmolLM2-CoT-360M
+ Fine-tune nB : prithivMLmods/SmolLM2-CoT-360M
🎯Fine-tuning SmolLM2 on a lightweight synthetic reasoning dataset for reasoning-specific tasks. Future updates will focus on lightweight, blazing-fast reasoning models. Until then, check out the blog for fine-tuning details.
🔥Blog : https://huggingface.co/blog/prithivMLmods/smollm2-ft
🔼 Models :
+ SmolLM2-CoT-360M : prithivMLmods/SmolLM2-CoT-360M
+ Reasoning-SmolLM2-135M : prithivMLmods/Reasoning-SmolLM2-135M
+ SmolLM2-CoT-360M-GGUF : prithivMLmods/SmolLM2-CoT-360M-GGUF
🤠 Other Details :
+ Demo : prithivMLmods/SmolLM2-CoT-360M
+ Fine-tune nB : prithivMLmods/SmolLM2-CoT-360M
reacted to
MonsterMMORPG's
post with ❤️
about 1 year ago
Post
3408
SANA: Ultra HD Fast Text to Image Model from NVIDIA Step by Step Tutorial on Windows, Cloud & Kaggle — Generate 2048x2048 Images
Below is YouTube link for step by step tutorial and a 1-Click to installer having very advanced Gradio APP to use newest Text-to-Image SANA Model on your Windows PC locally and also on cloud services such as Massed Compute, RunPod and free Kaggle.
https://youtu.be/KW-MHmoNcqo
This above tutorial covers the newest SANA 2K model and I predict SANA 4K model will be published as well. Sana 2K model is 4 MegaPixel so it can generate the following aspect ratio and resolutions very well:
“1:1”: (2048, 2048), “4:3”: (2304, 1792), “3:4”: (1792, 2304),
“3:2”: (2432, 1664), “2:3”: (1664, 2432), “16:9”: (2688, 1536),
“9:16”: (1536, 2688), “21:9”: (3072, 1280), “9:21”: (1280, 3072),
“4:5”: (1792, 2240), “5:4”: (2240, 1792)
I have developed an amazing Gradio app with so many new features :
VAE auto offloading to reduce VRAM usage significantly which is not exists on official pipeline
Gradio APP built upon official pipeline with improvements so works perfect
Batch size working perfect
Number of images working perfect
Multi-line prompting working perfect
Aspect ratios for both 1K and 2K models working perfect
Randomized seed working perfect
1-Click installers for Windows (using Python 3.10 and VENV — isolated), RunPod, Massed Compute and even a free Kaggle account notebook
With proper latest libraries working perfect speed on Windows too
Automatically properly saving every generated image into accurate folder
🔗 Full Instructions, Configs, Installers, Information and Links Shared Post (the one used in the tutorial) ⤵️
▶️ https://www.patreon.com/posts/click-to-open-post-used-in-tutorial-116474081
🔗 SECourses Official Discord 9500+ Members ⤵️
▶️ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
Below is YouTube link for step by step tutorial and a 1-Click to installer having very advanced Gradio APP to use newest Text-to-Image SANA Model on your Windows PC locally and also on cloud services such as Massed Compute, RunPod and free Kaggle.
https://youtu.be/KW-MHmoNcqo
This above tutorial covers the newest SANA 2K model and I predict SANA 4K model will be published as well. Sana 2K model is 4 MegaPixel so it can generate the following aspect ratio and resolutions very well:
“1:1”: (2048, 2048), “4:3”: (2304, 1792), “3:4”: (1792, 2304),
“3:2”: (2432, 1664), “2:3”: (1664, 2432), “16:9”: (2688, 1536),
“9:16”: (1536, 2688), “21:9”: (3072, 1280), “9:21”: (1280, 3072),
“4:5”: (1792, 2240), “5:4”: (2240, 1792)
I have developed an amazing Gradio app with so many new features :
VAE auto offloading to reduce VRAM usage significantly which is not exists on official pipeline
Gradio APP built upon official pipeline with improvements so works perfect
Batch size working perfect
Number of images working perfect
Multi-line prompting working perfect
Aspect ratios for both 1K and 2K models working perfect
Randomized seed working perfect
1-Click installers for Windows (using Python 3.10 and VENV — isolated), RunPod, Massed Compute and even a free Kaggle account notebook
With proper latest libraries working perfect speed on Windows too
Automatically properly saving every generated image into accurate folder
🔗 Full Instructions, Configs, Installers, Information and Links Shared Post (the one used in the tutorial) ⤵️
▶️ https://www.patreon.com/posts/click-to-open-post-used-in-tutorial-116474081
🔗 SECourses Official Discord 9500+ Members ⤵️
▶️ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
- 2 replies
reacted to
awacke1's
post with 👍
about 1 year ago
Post
2710
LLMs and LRMs - Logical Reasoning and Chain of Thought.
This is a read-aloud lecture to answer questions of using language reasoning techniques in advanced AGI style chain of thought AI pipelines.
Produced using DeepResearchEvaluator located here: awacke1/DeepResearchEvaluator
Videos:
https://x.com/Aaron_Wacker/status/1874835790087463063
https://www.youtube.com/watch?v=fW_A1hH_7RM
This is a read-aloud lecture to answer questions of using language reasoning techniques in advanced AGI style chain of thought AI pipelines.
Produced using DeepResearchEvaluator located here: awacke1/DeepResearchEvaluator
Videos:
https://x.com/Aaron_Wacker/status/1874835790087463063
https://www.youtube.com/watch?v=fW_A1hH_7RM
- 1 reply