metadata
base_model: deepseek-ai/DeepSeek-R1
language:
- en
library_name: transformers
tags:
- deepseek
- unsloth
- transformers
We are working on DeepSeek-R1 GGUFs. =)
See our collection for versions of Deepseek R1 including GGUF and original formats.
Finetune LLMs 2-5x faster with 70% less memory via Unsloth!
We have a free Google Colab Tesla T4 notebook for Llama 3.1 (8B) here: https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_(8B)-Alpaca.ipynb
unsloth/DeepSeek-R1
For more details on the model, please go to Deepseek's original model card
✨ Finetune for Free
All notebooks are beginner friendly! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model which can be exported to GGUF, vLLM or uploaded to Hugging Face.
| Unsloth supports | Free Notebooks | Performance | Memory use |
|---|---|---|---|
| Llama-3.2 (3B) | ▶️ Start on Colab | 2.4x faster | 58% less |
| Llama-3.2 (11B vision) | ▶️ Start on Colab | 2x faster | 60% less |
| Qwen2 VL (7B) | ▶️ Start on Colab | 1.8x faster | 60% less |
| Qwen2.5 (7B) | ▶️ Start on Colab | 2x faster | 60% less |
| Llama-3.1 (8B) | ▶️ Start on Colab | 2.4x faster | 58% less |
| Phi-3.5 (mini) | ▶️ Start on Colab | 2x faster | 50% less |
| Gemma 2 (9B) | ▶️ Start on Colab | 2.4x faster | 58% less |
| Mistral (7B) | ▶️ Start on Colab | 2.2x faster | 62% less |
- This Llama 3.2 conversational notebook is useful for ShareGPT ChatML / Vicuna templates.
- This text completion notebook is for raw text. This DPO notebook replicates Zephyr.
- * Kaggle has 2x T4s, but we use 1. Due to overhead, 1x T4 is 5x faster.
Special Thanks
A huge thank you to the DeepSeek team for creating and releasing these models.