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LFM2.5-2.6B: Deploy Agents Everywhere — Blog
LFM2.5-2.6B: Deploy Agents Everywhere — Blog
LFM2.5-2.6B is an on-device agentic model that plans, calls tools, and runs multi-step tasks at 220 tok/s in under 2.5 GB. Open weights on Hugging Face.
MOPD. We then use the specialized experts as teachers and distill their capabilities into a single student model. Unlike off-policy distillation, where the student learns from trajectories generated by another model, MOPD lets the student roll out under its own policy. Each prompt is routed to the teacher for its corresponding domain, which supervises the student's response with token-level feedback.
Model Factory
·liquid.ai·
LFM2.5-2.6B: Deploy Agents Everywhere — Blog
Understanding RAG vs Fine-Tuning
Understanding RAG vs Fine-Tuning
Discover the key differences between RAG and fine-tuning, what each approach can bring, and how to choose the right AI approach for your business goals.
ConceptConcept
·cohere.com·
Understanding RAG vs Fine-Tuning
"regular people don't fine-tune VLMs"
"regular people don't fine-tune VLMs"
but wtf not? - skill gap - high fine-tuning costs - lack of standards and unified approaches over the past few weeks I've been working on maestro - streamlined tool for VLM fine-tuning link: — SkalskiP (@skalskip92)
VLMVLM
·x.com·
"regular people don't fine-tune VLMs"
Fine Tune DeepSeek R1 | Build a Medical Chatbot
Fine Tune DeepSeek R1 | Build a Medical Chatbot
In this video, we show you how to fine-tune DeepSeek R1, an open-source reasoning model, using LoRA (Low-Rank Adaptation). We'll also be using Kaggle, Hugging Face and Weights & Biases. We walk you through data preparation, model configuration, and optimization, including advanced techniques like four-bit quantization for efficient training on consumer GPUs. By the end of this tutorial, you’ll be equipped with the skills to customize DeepSeek R1 for your own specialized tasks, such as medical reasoning. 🔗 Resources & Tutorials Kaggle Notebook: https://www.kaggle.com/code/aan1994/fine-tuning-deepseek-r1-reasoning-model-youtube How Transformers Work: https://www.datacamp.com/tutorial/how-transformers-work Fine-Tuning DeepSeek R1 Reasoning Model: https://www.datacamp.com/tutorial/fine-tuning-deepseek-r1-reasoning-model DeepSeek R1 Blog Overview: https://www.datacamp.com/blog/deepseek-r1 Understanding Janus Pro: https://www.datacamp.com/blog/janus-pro DeepSeek R1 Project Walkthrough: https://www.datacamp.com/tutorial/deepseek-r1-project DeepSeek vs ChatGPT: https://www.datacamp.com/blog/deepseek-vs-chatgpt Qwen-2.5 MAX Model: https://www.datacamp.com/blog/qwen-2-5-max DeepSeek R1 Ollama Tutorial: https://www.datacamp.com/tutorial/deepseek-r1-ollama 📕 Chapters 00:00 Introduction 00:30 Why Fine-Tuning DeepSeek Matters 02:30 LoRA Explained with a PS5 Factory Analogy 05:20 Tools & Setup Overview 09:00 Loading DeepSeek R1 Model and Tokenizer 16:10 Formatting Data for Fine-Tuning 23:00 Applying LoRA for Efficient Updates 34:00 Configuring Training Parameters 43:15 Running the Fine-Tuning Process on Kaggle 46:00 Comparing Model Performance After Fine-Tuning 47:50 Final Thoughts on Future Models 📱 Follow Us on Social Media Facebook: https://www.facebook.com/datacampinc/ Twitter: https://twitter.com/datacamp LinkedIn: https://www.linkedin.com/school/datacampinc/ Instagram: https://www.instagram.com/datacamp/ #deepseek #DeepSeekR1 #FineTuningAI #LearnAI #MachineLearning #Transformers #HuggingFace #Kaggle #WeightsAndBiases #LoRA #LargeLanguageModels #DeepSeekTutorial #AIResearch #AIOptimization #DataScience
·youtu.be·
Fine Tune DeepSeek R1 | Build a Medical Chatbot
transformerlab/transformerlab-app: Open Source Application for Advanced LLM Engineering: interact, train, fine-tune, and evaluate large language models on your own computer.
transformerlab/transformerlab-app: Open Source Application for Advanced LLM Engineering: interact, train, fine-tune, and evaluate large language models on your own computer.
Open Source Application for Advanced LLM Engineering: interact, train, fine-tune, and evaluate large language models on your own computer. - transformerlab/transformerlab-app
ConceptConcept
·t.co·
transformerlab/transformerlab-app: Open Source Application for Advanced LLM Engineering: interact, train, fine-tune, and evaluate large language models on your own computer.