Jean Louis

JLouisBiz

https://www.StartYourOwnGoldMine.com

AI & ML interests

- LLM for sales, marketing, promotion - LLM for Website Revision System - increasing quality of communication with customers - helping clients access information faster - saving people from financial troubles

Recent Activity

replied to danielhanchen's post about 16 hours ago

You can now fine-tune embedding models in our free Unsloth notebook! 🤗 Fine-tuning embedding models improves retrieval & RAG by aligning vectors to your domain-specific notion of similarity, improving search, clustering, and recommendations on your data. ⭐ Blog + Notebooks: https://unsloth.ai/docs/new/embedding-finetuning Unsloth trains embedding models 1.8-3.3x faster with 20% less VRAM, 2x longer context & no accuracy loss vs. FA2 setups. We'd like to thank Hugging Face and Unsloth contributor: electroglyph for making this possible!

replied to ronantakizawa's post 3 days ago

Moltbook, a Reddit platform only for AI agents, is going viral right now as agents are acting unhinged! I compiled a dataset of all posts and subreddits in Moltbook so far so anyone can easily analyze the activity in Moltbook. https://huggingface.co/datasets/ronantakizawa/moltbook #moltbook #clawd #aiagent

reacted to jorgemunozl's post with 👀 3 days ago

Test I know that it was buggy, OMG

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Organizations

replied to danielhanchen's post about 16 hours ago

I am interested to talk to you related to training of models, interested in paid service where I would need:

advice on the choice of the model to be trained;
advice on the creation of the datasets;
once I finish with the dataset, that I give it to you for training;

replied to ronantakizawa's post 3 days ago

agents are acting unhinged

No, agents are not beings.

Human are acting unhinged on the hype.

reacted to jorgemunozl's post with 👀 3 days ago

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Test

I know that it was buggy, OMG

reacted to MonsterMMORPG's post with 👍 3 days ago

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LTX 2 & Z Image Base Full Tutorial + Audio to Video Lip Sync + ComfyUI + SwarmUI + Windows + Cloud

Full tutorial link > https://www.youtube.com/watch?v=SkXrYezeEDc

Info
LTX 2 is the newest state of the art (SOTA) Open Source video generation model and tutorial will show you how to use it with very best and most performant way in ComfyUI and also in SwarmUI. Moreover, Z Image Base model published and I will show how to use Z Image Base with most amazing preset and workflow as well. Furthermore, this tutorial will show you how to install, update, setup, download ComfyUI and SwarmUI and models and presets and workflows both on Windows and on RunPod, Massed Compute and SimplePod. Linux users can use Massed Compute scripts and installers directly. This is a masterpiece entire lecture level complete tutorial. This video will kickstart your AI journey 100x. Both local Windows and Cloud.

45 Second Raw Demo Video

This video made with text + image + audio = lip synched and animated video at once

See video below

3 replies

reacted to Duskfallcrew's post with 👀 3 days ago

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You've noticed that I did the "WEIRD" and attempted to make it look like all my old content was "SCRAPED"

I'm largely retiring from GEN AI.

Calypso Crunchies is an old account I used to use for diffusers conversions for someone.

IF YOU WOULD LIKE ACCESS to ANYTHING -- I lost access due to me forgetting to jank Calypso into the E&D old repo, but i can get Angel or someone to add me or my other account back..

I didn't want HF to lose 3 years of my insane progress in doing things, but i need to retire from Generative image AI fast, my mental health has been diving for so long.

I'll continue in the developing/vibe coding./educational sphere, but I just can't continue in the other end of it. Much love, thank you all

2 replies

replied to OzTianlu's post 3 days ago

Браво мајстори, само напријед.

reacted to OzTianlu's post with 👍 3 days ago

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Geilim-1B-SR-Instruct — Serbian Intelligence for Deep Reasoning 🧠🇷🇸
NoesisLab/Geilim-1B-SR-Instruct
Geilim-1B-SR-Instruct is a lightweight Large Language Model (LLM) designed to bring advanced reasoning capabilities to low-resource languages. It focuses on Serbian understanding and generation while maintaining robust English reasoning. Built on the LLaMA-3 architecture with a proprietary hybrid reasoning mechanism, it delivers deep logic while keeping outputs concise and natural. 🚀

Core Innovations 💡

Implicit Deep Reasoning: Combines standard attention mechanisms with graph-structured reasoning components for rigorous logic and causal inference. 🕸️

ASPP & -flow Hybrid Design: High-efficiency structured propagation + internal probability space optimization for high-quality reasoning without long-winded intermediate steps. ⚡
Bilingual Adaptation: Primarily focused on Serbian while preserving English logic, making it perfect for multilingual chats and cross-lingual tasks. 🌍
Lightweight & Efficient: At ~1.3B parameters, it runs smoothly on consumer-grade GPUs, ideal for edge devices and research. 💻

Use Cases 🛠️

Serbian Chatbots: Intelligent assistants with local linguistic nuance. 🗣️
Educational Tools: Multi-turn interactive tasks and learning support. 📚

Key Advantages ✨

Clean Output: Avoids messy "thinking" tags; reasoning happens internally, delivering clear and direct results. ✅
Open Access: Licensed under Apache-2.0, making it easy for research and engineering integration. 🔓
AI Democratization: Empowering low-resource language ecosystems with cutting-edge intelligence. 🤝

1 reply

liked a model 3 days ago

unsloth/Ministral-3-14B-Instruct-2512-GGUF

14B • Updated Dec 4, 2025 • 19.6k • 61

reacted to eaddario's post with 👍 3 days ago

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Experimental global target bits‑per‑weight quantization of mistralai/Ministral-3-14B-Instruct-2512 and mistralai/Ministral-3-14B-Reasoning-2512

Unlike standard llama.cpp quantizations that rely on fixed type heuristics (e.g., Q4_K_M), the Target BPW approach optimizes per-tensor precision where it matters the most, and produces high quality models that meet a precise global file size target.

Key Advantages:
- VRAM Maximization: Can generate high quality models sized exactly to fit hardware constraints (e.g., fitting the model into exactly 24GB VRAM).
- Data-Driven Precision: Quantization mix is determined by actual weight error sensitivity rather than hardcoded rules, often yielding better PPL/KLD size trade-offs.

Full benchmarks (PPL, KLD, ARC, MMLU, etc.) and methodology in the models' cards

eaddario/Ministral-3-14B-Instruct-2512-GGUF
eaddario/Ministral-3-14B-Reasoning-2512-GGUF