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--- |
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base_model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF |
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datasets: |
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- nvidia/HelpSteer2 |
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language: |
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- en |
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library_name: transformers |
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license: llama3.1 |
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pipeline_tag: text-generation |
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tags: |
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- nvidia |
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- llama3.1 |
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- unsloth |
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- llama |
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--- |
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# Finetune Llama 3.2, NVIDIA Nemotron, Mistral 2-5x faster with 70% less memory via Unsloth! |
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We have a free Google Colab Tesla T4 notebook for Llama 3.2 (3B) here: https://colab.research.google.com/drive/1Ys44kVvmeZtnICzWz0xgpRnrIOjZAuxp?usp=sharing |
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/>](https://discord.gg/unsloth) |
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
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# unsloth/Llama-3.1-Nemotron-70B-Instruct-GGUF |
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For more details on the model, please go to NVIDIA's original [model card](https://huggingface.co/nvidia/Llama-3.1-Nemotron-70B-Instruct-HF) |
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## ✨ Finetune for Free |
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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. |
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| Unsloth supports | Free Notebooks | Performance | Memory use | |
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|-----------------|--------------------------------------------------------------------------------------------------------------------------|-------------|----------| |
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| **Llama-3.2 (3B)** | [▶️ Start on Colab](https://colab.research.google.com/drive/1Ys44kVvmeZtnICzWz0xgpRnrIOjZAuxp?usp=sharing) | 2.4x faster | 58% less | |
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| **Llama-3.1 (8B)** | [▶️ Start on Colab](https://colab.research.google.com/drive/1Ys44kVvmeZtnICzWz0xgpRnrIOjZAuxp?usp=sharing) | 2.4x faster | 58% less | |
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| **Phi-3.5 (mini)** | [▶️ Start on Colab](https://colab.research.google.com/drive/1lN6hPQveB_mHSnTOYifygFcrO8C1bxq4?usp=sharing) | 2x faster | 50% less | |
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| **Gemma 2 (9B)** | [▶️ Start on Colab](https://colab.research.google.com/drive/1vIrqH5uYDQwsJ4-OO3DErvuv4pBgVwk4?usp=sharing) | 2.4x faster | 58% less | |
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| **Mistral (7B)** | [▶️ Start on Colab](https://colab.research.google.com/drive/1Dyauq4kTZoLewQ1cApceUQVNcnnNTzg_?usp=sharing) | 2.2x faster | 62% less | |
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| **DPO - Zephyr** | [▶️ Start on Colab](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing) | 1.9x faster | 19% less | |
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- This [conversational notebook](https://colab.research.google.com/drive/1Aau3lgPzeZKQ-98h69CCu1UJcvIBLmy2?usp=sharing) is useful for ShareGPT ChatML / Vicuna templates. |
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- This [text completion notebook](https://colab.research.google.com/drive/1ef-tab5bhkvWmBOObepl1WgJvfvSzn5Q?usp=sharing) is for raw text. This [DPO notebook](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing) replicates Zephyr. |
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- \* Kaggle has 2x T4s, but we use 1. Due to overhead, 1x T4 is 5x faster. |
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## Special Thanks |
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A huge thank you to the Meta and Llama team for creating these models and for NVIDIA fine-tuning them and releasing them. |
