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finetuning LLMs will never be the same! Unsloth just launched an open-source web UI to run and fine-tune 500+ LLMs without writing any code. key features - run models locally on Mac, Windows, Linux - train 500+ models 2x faster with 70% less VRAM - supports GGUF, vision, audio,...

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Akshay 🚀

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45,225 görüntüleme • 2 ay önce •via X (Twitter)

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Introducing Unsloth Studio ✨ A new open-source web UI to train and run LLMs. • Run models locally on Mac, Windows, Linux • Train 500+ models 2x faster with 70% less VRAM • Supports GGUF, vision, audio, embedding models • Auto-create datasets from PDF, CSV, DOCX • Self-healing tool calling and code execution • Compare models side by side + export to GGUF GitHub: Blog and Guide: Available now on Hugging Face, NVIDIA, Docker and Colab.
0:45

Introducing Unsloth Studio ✨ A new open-source web UI to train and run LLMs. • Run models locally on Mac, Windows, Linux • Train 500+ models 2x faster with 70% less VRAM • Supports GGUF, vision, audio, embedding models • Auto-create datasets from PDF, CSV, DOCX • Self-healing tool calling and code execution • Compare models side by side + export to GGUF GitHub: Blog and Guide: Available now on Hugging Face, NVIDIA, Docker and Colab.

Unsloth AI

1,671,822 görüntüleme • 3 ay önce

Fine-tune 100+ LLMs directly from a UI! LLaMA-Factory lets you train and fine-tune open-source LLMs and VLMs without writing any code. Supports 100+ models, multimodal fine-tuning, PPO, DPO, experiment tracking, and much more! 100% open-source with 50k stars!
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Fine-tune 100+ LLMs directly from a UI! LLaMA-Factory lets you train and fine-tune open-source LLMs and VLMs without writing any code. Supports 100+ models, multimodal fine-tuning, PPO, DPO, experiment tracking, and much more! 100% open-source with 50k stars!

Avi Chawla

557,355 görüntüleme • 1 yıl önce

Fine-tune 100+ LLMs directly from a UI! LLaMA-Factory lets you train and fine-tune open-source LLMs and VLMs without writing any code. Supports 100+ models, multimodal fine-tuning, PPO, DPO, experiment tracking, and much more! 100% open-source, 51k+ stars 🌟
0:46

Fine-tune 100+ LLMs directly from a UI! LLaMA-Factory lets you train and fine-tune open-source LLMs and VLMs without writing any code. Supports 100+ models, multimodal fine-tuning, PPO, DPO, experiment tracking, and much more! 100% open-source, 51k+ stars 🌟

Akshay 🚀

60,163 görüntüleme • 1 yıl önce

You can now fine-tune TTS models with Unsloth! Train, run and save models like Sesame-CSM and OpenAI's Whisper locally with our free notebooks. Unsloth makes TTS training 1.5x faster with 50% less VRAM. GitHub: Docs & Notebooks:
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You can now fine-tune TTS models with Unsloth! Train, run and save models like Sesame-CSM and OpenAI's Whisper locally with our free notebooks. Unsloth makes TTS training 1.5x faster with 50% less VRAM. GitHub: Docs & Notebooks:

Unsloth AI

126,049 görüntüleme • 1 yıl önce

🚀 Just launched: The GitHub Models repo integration is in public preview. ✨ Now you can: ➡️ Version, review, and collaborate on .prompt.yml files just like code. ➡️ Compare outputs side-by-side from 40+ leading LLMs. ➡️ Easily set up with a single API key for FREE. ➡️ Benefit from enterprise-ready governance and security on GitHub and Azure. Ready to start building efficiently with AI models? Get started. 👇
2:06

🚀 Just launched: The GitHub Models repo integration is in public preview. ✨ Now you can: ➡️ Version, review, and collaborate on .prompt.yml files just like code. ➡️ Compare outputs side-by-side from 40+ leading LLMs. ➡️ Easily set up with a single API key for FREE. ➡️ Benefit from enterprise-ready governance and security on GitHub and Azure. Ready to start building efficiently with AI models? Get started. 👇

GitHub

37,217 görüntüleme • 1 yıl önce

You can now run GPT, Claude & other models in Unsloth. Connect + run APIs in a local UI: - Code execution, web search, image gen, editing - Auto prompt caching to save costs - Provider features like cites, sandboxes GitHub: Guide:
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You can now run GPT, Claude & other models in Unsloth. Connect + run APIs in a local UI: - Code execution, web search, image gen, editing - Auto prompt caching to save costs - Provider features like cites, sandboxes GitHub: Guide:

Unsloth AI

29,427 görüntüleme • 20 gün önce

You can now run Claude Code locally for FREE. → Using open-source models → Locally and fully private → Full agent + tool workflows Here's the FULL step-by-step tutorial to get it all set up in less than 10 minutes:
8:32

You can now run Claude Code locally for FREE. → Using open-source models → Locally and fully private → Full agent + tool workflows Here's the FULL step-by-step tutorial to get it all set up in less than 10 minutes:

Alvaro Cintas

1,314,914 görüntüleme • 4 ay önce

🎨 Introducing fal Sandbox. You can now instantly run the same input across multiple models. Compare hundreds of models from fal’s platform side-by-side for speed, quality, and cost.
0:30

🎨 Introducing fal Sandbox. You can now instantly run the same input across multiple models. Compare hundreds of models from fal’s platform side-by-side for speed, quality, and cost.

fal

816,744 görüntüleme • 8 ay önce

Watch this 45 min video to learn how to create synthetic datasets and train tiny (100M params) local language models that expertise on narrow tasks. Code, datasets, models, harnesses all in comments.
46:40

Watch this 45 min video to learn how to create synthetic datasets and train tiny (100M params) local language models that expertise on narrow tasks. Code, datasets, models, harnesses all in comments.

AVB

35,225 görüntüleme • 18 gün önce

Ollama 0.2 is here! Concurrency is now enabled by default. This unlocks 2 major features: Parallel requests Ollama can now serve multiple requests at the same time, using only a little bit of additional memory for each request. This enables use cases such as: - Handling multiple chat sessions at the same time - Hosting code completion LLMs for your team - Processing different parts of a document simultaneously - Running multiple agents at the same time Run multiple models Ollama now supports loading different models at the same time. This improves several use cases: - Retrieval Augmented Generation (RAG): both the embedding and text completion models can be loaded into memory simultaneously. - Agents: multiple versions of an agent can now run simultaneously - Running large and small models side-by-side Models are automatically loaded and unloaded based on requests and how much GPU memory is available.
0:23

Ollama 0.2 is here! Concurrency is now enabled by default. This unlocks 2 major features: Parallel requests Ollama can now serve multiple requests at the same time, using only a little bit of additional memory for each request. This enables use cases such as: - Handling multiple chat sessions at the same time - Hosting code completion LLMs for your team - Processing different parts of a document simultaneously - Running multiple agents at the same time Run multiple models Ollama now supports loading different models at the same time. This improves several use cases: - Retrieval Augmented Generation (RAG): both the embedding and text completion models can be loaded into memory simultaneously. - Agents: multiple versions of an agent can now run simultaneously - Running large and small models side-by-side Models are automatically loaded and unloaded based on requests and how much GPU memory is available.

ollama

219,369 görüntüleme • 1 yıl önce

The future of AI is open-source. And ollama is the easiest way to build AI applications with open-source LLMs. Here's how to build a free, private RAG app using open-source tools. We'll use: - Ollama for LLMs and embedding models - PostgreSQL for data storage and retrieval - pgai Vectorizer for embedding creation and sync (I use Nomic for embeddings and tinnyllama as my LLM but you can substitute them for any models on Ollama)
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The future of AI is open-source. And ollama is the easiest way to build AI applications with open-source LLMs. Here's how to build a free, private RAG app using open-source tools. We'll use: - Ollama for LLMs and embedding models - PostgreSQL for data storage and retrieval - pgai Vectorizer for embedding creation and sync (I use Nomic for embeddings and tinnyllama as my LLM but you can substitute them for any models on Ollama)

Avthar

34,261 görüntüleme • 1 yıl önce

OpenAI CPO, Kevin Weil: Humans have a strong desire to build and create, even in the age of AGI models will teach new skills and enable more people to create. you might write less code, but you’ll still be managing the models, writing code, and staying technical
1:04

OpenAI CPO, Kevin Weil: Humans have a strong desire to build and create, even in the age of AGI models will teach new skills and enable more people to create. you might write less code, but you’ll still be managing the models, writing code, and staying technical

Haider.

19,391 görüntüleme • 1 yıl önce

Create datasets, run evals, and even train models directly in Cursor with the Hugging Face plugin. Here's Ben Burtenshaw to show you how:
1:53

Create datasets, run evals, and even train models directly in Cursor with the Hugging Face plugin. Here's Ben Burtenshaw to show you how:

edwin

17,119 görüntüleme • 3 ay önce

Open Interpreter's new release looks great for locally running LLMs The tool lets LLMs run code (Python, Javascript, Shell, and more) locally. You can chat with Open Interpreter through a ChatGPT-like interface in your terminal by running $ interpreter after installing. Just do `pip install open-interpreter` and then just run `- interpreter --local` sets up fast, local LLMs. Congrats killian 👏
1:23

Open Interpreter's new release looks great for locally running LLMs The tool lets LLMs run code (Python, Javascript, Shell, and more) locally. You can chat with Open Interpreter through a ChatGPT-like interface in your terminal by running $ interpreter after installing. Just do `pip install open-interpreter` and then just run `- interpreter --local` sets up fast, local LLMs. Congrats killian 👏

Rohan Paul

153,351 görüntüleme • 2 yıl önce

Genspark has released a new AI browser that gives you access to: - 169 open source models that run LOCALLY - Automation of browsing and workflows - Agents on any page And much more. Available on Mac and Windows (use cases below)
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Genspark has released a new AI browser that gives you access to: - 169 open source models that run LOCALLY - Automation of browsing and workflows - Agents on any page And much more. Available on Mac and Windows (use cases below)

Paul Couvert

80,819 görüntüleme • 9 ay önce

Run state-of-the-art RAG applications locally on your computer with ollama and use all the fantastic open-source models like llama3, msk's awesome models, or Command R from cohere With Verba 1.0, we put it all in your hands 🙌 Get on board for a wild open-source ride, we're bridging any moat as open-source is here to win
0:29

Run state-of-the-art RAG applications locally on your computer with ollama and use all the fantastic open-source models like llama3, msk's awesome models, or Command R from cohere With Verba 1.0, we put it all in your hands 🙌 Get on board for a wild open-source ride, we're bridging any moat as open-source is here to win

Philip Vollet

41,375 görüntüleme • 2 yıl önce

Run OpenClaw locally with ollama 🦙 – Open source models: MiniMax, Qwen, Kimi and more – One click install on macOS and Windows – Local & cloud Ollama models connected atomicbot.ai where llamas meet claws 🦞
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Run OpenClaw locally with ollama 🦙 – Open source models: MiniMax, Qwen, Kimi and more – One click install on macOS and Windows – Local & cloud Ollama models connected atomicbot.ai where llamas meet claws 🦞

atomicbot.ai

58,619 görüntüleme • 2 ay önce

4-bit Qwen3.6 MTP GGUF managed to search 70+ sites from a single prompt. Try this locally on 20GB RAM via Unsloth Studio. Unsloth now supports auto MTP + speculative decoding & auto-selects the best MTP settings for your device (Mac, CPU, GPU). GitHub:
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4-bit Qwen3.6 MTP GGUF managed to search 70+ sites from a single prompt. Try this locally on 20GB RAM via Unsloth Studio. Unsloth now supports auto MTP + speculative decoding & auto-selects the best MTP settings for your device (Mac, CPU, GPU). GitHub:

Unsloth AI

71,624 görüntüleme • 27 gün önce

Introducing FoundationMotion. A large-scale, video-derived motion annotation dataset & auto-labeling pipeline + advanced models for motion understanding. Fully open-source: code, datasets, and models, free to use and build on. Understanding motion is core to physical reasoning, yet today’s leading models still struggle with simple spatial actions like “turn right” or “move up” or “flip the toast” - mainly due to the lack of large, fine-grained motion datasets. We present FoundationMotion, a fully automated pipeline that: • detects & tracks objects in videos • extracts trajectories • uses LLMs + frames to generate rich motion captions & QA pairs → creating large-scale, high-quality motion datasets at scale. After fine-tuning the open-source models Qwen and NVILA on our annotations, these models now outperform the closed-source Gemini-3-Flash and GPT-5.1 on spatial understanding tasks across autonomous driving, robotics, and everyday scenarios. 📜Paper: 🌐Webpage: 💻 Code: 🕸️Model: 📊 Dataset: 👉 Interactive Demo: Let’s move research forward together. FoundationMotion is also referred to as Wolf V2 🐺, the second chapter in the Wolf series:
1:25

Introducing FoundationMotion. A large-scale, video-derived motion annotation dataset & auto-labeling pipeline + advanced models for motion understanding. Fully open-source: code, datasets, and models, free to use and build on. Understanding motion is core to physical reasoning, yet today’s leading models still struggle with simple spatial actions like “turn right” or “move up” or “flip the toast” - mainly due to the lack of large, fine-grained motion datasets. We present FoundationMotion, a fully automated pipeline that: • detects & tracks objects in videos • extracts trajectories • uses LLMs + frames to generate rich motion captions & QA pairs → creating large-scale, high-quality motion datasets at scale. After fine-tuning the open-source models Qwen and NVILA on our annotations, these models now outperform the closed-source Gemini-3-Flash and GPT-5.1 on spatial understanding tasks across autonomous driving, robotics, and everyday scenarios. 📜Paper: 🌐Webpage: 💻 Code: 🕸️Model: 📊 Dataset: 👉 Interactive Demo: Let’s move research forward together. FoundationMotion is also referred to as Wolf V2 🐺, the second chapter in the Wolf series:

Boyi Li

66,637 görüntüleme • 6 ay önce

꧁IP꧂ encompasses all data used to fuel AI models. On Story, anyone can register open source AI models, data sets, and fine tune their models. AI cannot exist without IP, and Story makes IP programmable.
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꧁IP꧂ encompasses all data used to fuel AI models. On Story, anyone can register open source AI models, data sets, and fine tune their models. AI cannot exist without IP, and Story makes IP programmable.

Story

155,404 görüntüleme • 1 yıl önce