DVC
Open-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments.
We’re thrilled to welcome the DVC Community to the lakeFS family. Keep updated on blog posts with our RSS Feed! We use cookies to improve your experience and understand how our site is used. Learn more in our Privacy Policy We provide short articles on common data science scenarios where DVC can help. Our example scenarios are not written to be run end-to-end like tutorials. For more hands-on experience with DVC, see Get Started. Even with all the success we've seen in machine learning, especially with deep learning and its applications in business, data scientists still lack best practices for organizing their projects and collaborating effectively. This is a critical challenge: while ML algorithms and methods are no longer tribal knowledge, they are still difficult to develop, reuse, and manage. If you store and process data files or datasets to produce other data or machine learning models, and you want to Choose a page from the navigation sidebar to the left. ✅ Check out our GitHub repositories: DVC give us a ⭐ if you like the project! We use cookies to improve your experience and understand how our site is used. Learn more in our Privacy Policy
Unsloth
Unsloth is an open-source, no-code web UI for training, running and exporting open models in one unified local interface.
Unsloth lets you run and train AI models on your own local hardware. Run and train Google's new Gemma 4 models! A new open, no-code web UI to train and run LLMs. New Qwen3.5 Small Medium LLMs are here! Run the new 4B and 120B models by NVIDIA. Train MoE LLMs 12x faster with less VRAM. Learn to run local LLMs via Claude OpenAI. Run fine-tune the new 80B coding model. Run fine-tune 30B model for agentic coding. Unsloth streamlines local training, inference, data, and deployment Search + download + run any model like GGUFs, LoRA adapters, safetensors. Train and RL 500+ models ~2x faster with ~70% less VRAM (no accuracy loss) Supports full fine-tuning, pre-training, 4-bit, 16-bit and FP8 training. Enables LLMs to predict if a headline impacts a company positively or negatively. Can use historical customer interactions for more accurate and custom responses. Fine-tune LLM on legal texts for contract analysis, case law research, and compliance. You can think of a fine-tuned model as a specialized agent designed to do specific tasks more effectively and efficiently. Fine-tuning can replicate all of RAG's capabilities, but not vice versa.
DVC
Unsloth
DVC
Unsloth
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DVC
Unsloth
DVC
Unsloth
