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unsloth / SmolLM2-135M-Instruct-GGUF
Model's Last Updated: November 01 2024
Introduction of SmolLM2-135M-Instruct-GGUF
Model Details of SmolLM2-135M-Instruct-GGUF
Finetune SmolLM2, Llama 3.2, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a free Google Colab Tesla T4 notebook for Llama 3.2 (3B) here: https://colab.research.google.com/drive/1Ys44kVvmeZtnICzWz0xgpRnrIOjZAuxp?usp=sharing
unsloth/SmolLM2-135M-Instruct-GGUF
For more details on the model, please go to Hugging Face'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 | 2.4x faster | 58% 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 |
| DPO - Zephyr | ▶️ Start on Colab | 1.9x faster | 19% less |
- This 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 Hugging Face team for creating and releasing these models.
Model Summary
SmolLM2 is a family of compact language models available in three size: 135M, 360M, and 1.7B parameters. They are capable of solving a wide range of tasks while being lightweight enough to run on-device.
The 1.7B variant demonstrates significant advances over its predecessor SmolLM1-1.7B, particularly in instruction following, knowledge, reasoning, and mathematics. It was trained on 11 trillion tokens using a diverse dataset combination: FineWeb-Edu, DCLM, The Stack, along with new mathematics and coding datasets that we curated and will release soon. We developed the instruct version through supervised fine-tuning (SFT) using a combination of public datasets and our own curated datasets. We then applied Direct Preference Optimization (DPO) using UltraFeedback .
The instruct model additionally supports tasks such as text rewriting, summarization and function calling thanks to datasets developed by Argilla such as Synth-APIGen-v0.1 .
SmolLM2
Runs of unsloth SmolLM2-135M-Instruct-GGUF on huggingface.co
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More Information About SmolLM2-135M-Instruct-GGUF huggingface.co Model
Url of SmolLM2-135M-Instruct-GGUF
SmolLM2-135M-Instruct-GGUF huggingface.co Url
Provider of SmolLM2-135M-Instruct-GGUF huggingface.co
Other API from unsloth
Updated:January 30 2026
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