From 4ac9529cc0194ea2e88d350bb871565144082b7c Mon Sep 17 00:00:00 2001 From: Michael Han <107991372+shimmyshimmer@users.noreply.github.com> Date: Mon, 5 May 2025 20:56:01 -0700 Subject: [PATCH] Update README.md Adding extra synthetic data notebook, cleaning repo --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 2332082866..d3e344550f 100644 --- a/README.md +++ b/README.md @@ -34,7 +34,8 @@ Notebooks are beginner friendly. Read our [guide](https://docs.unsloth.ai/get-st | **DPO Zephyr** | [▢️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Zephyr_(7B)-DPO.ipynb) | 1.9x faster | 50% less | - See [all our notebooks](https://docs.unsloth.ai/get-started/unsloth-notebooks) and [all our models](https://docs.unsloth.ai/get-started/all-our-models) -- **Kaggle Notebooks** for [Llama 3.2 Kaggle notebook](https://www.kaggle.com/danielhanchen/kaggle-llama-3-2-1b-3b-unsloth-notebook), [Llama 3.1 (8B)](https://www.kaggle.com/danielhanchen/kaggle-llama-3-1-8b-unsloth-notebook), [Phi-4 (14B)](https://www.kaggle.com/code/danielhanchen/phi-4-finetuning-unsloth-notebook), [Mistral (7B)](https://www.kaggle.com/code/danielhanchen/kaggle-mistral-7b-unsloth-notebook) +- **Kaggle Notebooks** for [Llama 3.2](https://www.kaggle.com/danielhanchen/kaggle-llama-3-2-1b-3b-unsloth-notebook), [Llama 3.1 (8B)](https://www.kaggle.com/danielhanchen/kaggle-llama-3-1-8b-unsloth-notebook), [Phi-4 (14B)](https://www.kaggle.com/code/danielhanchen/phi-4-finetuning-unsloth-notebook), [Mistral (7B)](https://www.kaggle.com/code/danielhanchen/kaggle-mistral-7b-unsloth-notebook) +- Don't have data? Use our [Synthetic Dataset notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Meta_Synthetic_Data_Llama3_2_(3B).ipynb) in collaboration with Meta. - See detailed documentation for Unsloth [here](https://docs.unsloth.ai/). ## ⚑ Quickstart @@ -52,12 +53,12 @@ For Windows install instructions, see [here](https://docs.unsloth.ai/get-started - πŸ“£ NEW! [**EVERYTHING** is now supported](https://unsloth.ai/blog/gemma3#everything) incuding: FFT, ALL models (Mixtral, MOE, Cohere, Mamba) and all training algorithms (KTO, DoRA) etc. MultiGPU support coming very soon. To enable full-finetuning, set ```full_finetuning = True``` and for 8-bit finetuning, set ```load_in_8bit = True``` - πŸ“£ **Gemma 3** by Google: [Read Blog](https://unsloth.ai/blog/gemma3). We [uploaded GGUFs, 4-bit models](https://huggingface.co/collections/unsloth/gemma-3-67d12b7e8816ec6efa7e4e5b). -- πŸ“£ NEW! Introducing Long-context [Reasoning (GRPO)](https://unsloth.ai/blog/grpo) in Unsloth. Train your own reasoning model with just 5GB VRAM. Transform Llama, Phi, Mistral etc. into reasoning LLMs! +- πŸ“£ Introducing Long-context [Reasoning (GRPO)](https://unsloth.ai/blog/grpo) in Unsloth. Train your own reasoning model with just 5GB VRAM. Transform Llama, Phi, Mistral etc. into reasoning LLMs! - πŸ“£ [DeepSeek-R1](https://unsloth.ai/blog/deepseek-r1) - the most powerful open reasoning models with Llama & Qwen distillations. Run or fine-tune them now [with our guide](https://unsloth.ai/blog/deepseek-r1). All model uploads: [here](https://huggingface.co/collections/unsloth/deepseek-r1-all-versions-678e1c48f5d2fce87892ace5). -- πŸ“£ Introducing Unsloth [Dynamic 4-bit Quantization](https://unsloth.ai/blog/dynamic-4bit)! We dynamically opt not to quantize certain parameters and this greatly increases accuracy while only using <10% more VRAM than BnB 4-bit. See our collection on [Hugging Face here.](https://huggingface.co/collections/unsloth/unsloth-4-bit-dynamic-quants-67503bb873f89e15276c44e7)
Click for more news +- πŸ“£ Introducing Unsloth [Dynamic 4-bit Quantization](https://unsloth.ai/blog/dynamic-4bit)! We dynamically opt not to quantize certain parameters and this greatly increases accuracy while only using <10% more VRAM than BnB 4-bit. See our collection on [Hugging Face here.](https://huggingface.co/collections/unsloth/unsloth-4-bit-dynamic-quants-67503bb873f89e15276c44e7) - πŸ“£ [Phi-4](https://unsloth.ai/blog/phi4) by Microsoft: We also [fixed bugs](https://unsloth.ai/blog/phi4) in Phi-4 and [uploaded GGUFs, 4-bit](https://huggingface.co/collections/unsloth/phi-4-all-versions-677eecf93784e61afe762afa). - πŸ“£ [Vision models](https://unsloth.ai/blog/vision) now supported! [Llama 3.2 Vision (11B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_(11B)-Vision.ipynb), [Qwen 2.5 VL (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2_VL_(7B)-Vision.ipynb) and [Pixtral (12B) 2409](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Pixtral_(12B)-Vision.ipynb) - πŸ“£ [Llama 3.3 (70B)](https://huggingface.co/collections/unsloth/llama-33-all-versions-67535d7d994794b9d7cf5e9f), Meta's latest model is supported. @@ -88,7 +89,6 @@ For Windows install instructions, see [here](https://docs.unsloth.ai/get-started - **0% loss in accuracy** - no approximation methods - all exact. - No change of hardware. Supports NVIDIA GPUs since 2018+. Minimum CUDA Capability 7.0 (V100, T4, Titan V, RTX 20, 30, 40x, A100, H100, L40 etc) [Check your GPU!](https://developer.nvidia.com/cuda-gpus) GTX 1070, 1080 works, but is slow. - Works on **Linux** and **Windows** -- Supports 4bit and 16bit QLoRA / LoRA finetuning via [bitsandbytes](https://github.com/TimDettmers/bitsandbytes). - If you trained a model with πŸ¦₯Unsloth, you can use this cool sticker!   ## πŸ’Ύ Install Unsloth