| --- |
| library_name: transformers |
| license: apache-2.0 |
| datasets: |
| - HuggingFaceTB/smoltalk |
| - HuggingFaceH4/ultrafeedback_binarized |
| base_model: |
| - SmallDoge/Doge-320M |
| language: |
| - en |
| pipeline_tag: question-answering |
| tags: |
| - trl |
| - sft |
| - dpo |
| - doge |
| --- |
| |
|
|
| # **Doge 320M Instruct** |
|
|
| <div align="center"> |
| <img src="https://huggingface.co/spaces/SmallDoge/README/resolve/main/org_icon.png" width="100%" alt="SmallDoge" /> |
| </div> |
| <hr> |
| <div align="center"> |
| <a href="https://discord.gg/P2yYH95N" target="_blank" style="margin: 2px;"> |
| <img alt="Discord" src="https://img.shields.io/badge/Discord-Small%20Doges-7289da?logo=discord&logoColor=white&color=7289da" style="display: inline-block; vertical-align: middle;"/> |
| </a> |
| <!-- <a href="https://arxiv.org/abs/2412.11834" target="_blank" style="margin: 2px;"> |
| <img alt="arXiv" src="https://img.shields.io/static/v1?label=arXiv&message=2412.11834&color=B31B1B&logo=arXiv" style="display: inline-block; vertical-align: middle;"/> |
| </a> --> |
| <a href="https://github.com/SmallDoges/small-doge" target="_blank" style="margin: 2px;"> |
| <img alt="GitHub" src="https://img.shields.io/badge/GitHub-SmallDoge-181717?logo=github" style="display: inline-block; vertical-align: middle;"/> |
| </a> |
| <a href="https://github.com/SmallDoges/small-doge/blob/main/LICENSE" style="margin: 2px;"> |
| <img alt="License" src="https://img.shields.io/badge/License-Apache--2.0-blue.svg" style="display: inline-block; vertical-align: middle;"/> |
| </a> |
| </div> |
| |
| Doge uses Dynamic Mask Attention as sequence transformation and can use Multi-Layer Perceptron or Cross Domain Mixture of Experts as state transformation. Dynamic Mask Attention allows the Transformer to use self-attention during training and state space during inference, and Cross Domain Mixture of Experts can directly inherit the weights of Multi-Layer Perceptron for further training. This model is trained by [SmallDoge](https://huggingface.co/SmallDoge) community, for detailed algorithm and model architecture, paper coming soon, all training details and code are available in the [small-doge](https://github.com/SmallDoges/small-doge) repository. |
|
|
|
|
| ## Uses |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig, TextStreamer |
| |
| tokenizer = AutoTokenizer.from_pretrained("SmallDoge/Doge-320M-Instruct") |
| model = AutoModelForCausalLM.from_pretrained("SmallDoge/Doge-320M-Instruct", trust_remote_code=True) |
| |
| generation_config = GenerationConfig( |
| max_new_tokens=100, |
| use_cache=True, |
| do_sample=True, |
| temperature=0.8, |
| top_p=0.9, |
| repetition_penalty=1.0 |
| ) |
| steamer = TextStreamer( |
| tokenizer=tokenizer, |
| skip_prompt=True |
| ) |
| |
| prompt = "Hi, how are you doing today?" |
| conversation = [ |
| {"role": "user", "content": prompt} |
| ] |
| inputs = tokenizer.apply_chat_template( |
| conversation=conversation, |
| tokenize=True, |
| return_tensors="pt", |
| ) |
| |
| outputs = model.generate( |
| inputs, |
| tokenizer=tokenizer, |
| generation_config=generation_config, |
| streamer=steamer |
| ) |
| ``` |
|
|
|
|
| ## Model Details |
|
|
| We build the Doge-Instruct by first SFT on [SmolTalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk) and then DPO on [UltraFeedback Binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized). |
|
|
| **SFT**: |
| | Model | Training Data | Epochs | Content Length | LR | Batch Size | Precision | |
| |---|---|---|---|---|---|---| |
| | [Doge-20M-Instruct-SFT](https://huggingface.co/SmallDoge/Doge-20M-Instruct-SFT) | [smoltalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk) | 2 | 2048 | 8e-4 | 0.25M | bfloat16 | |
| | [Doge-20M-MoE-Instruct-SFT](https://huggingface.co/SmallDoge/Doge-20M-MoE-Instruct-SFT) | [smoltalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk) | 2 | 2048 | 8e-4 | 0.25M | bfloat16 | |
| | [Doge-60M-Instruct-SFT](https://huggingface.co/SmallDoge/Doge-60M-Instruct-SFT) | [smoltalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk) | 2 | 2048 | 6e-4 | 0.25M | bfloat16 | |
| | [Doge-120M-MoE-Instruct-SFT](https://huggingface.co/SmallDoge/Doge-120M-MoE-Instruct-SFT) | [smoltalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk) | 2 | 2048 | 6e-4 | 0.25M | bfloat16 | |
| | [Doge-160M-Instruct-SFT](https://huggingface.co/SmallDoge/Doge-160M-Instruct-SFT) | [smoltalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk) | 2 | 2048 | 4e-4 | 0.25M | bfloat16 | |
| | [Doge-320M-Instruct-SFT](https://huggingface.co/SmallDoge/Doge-320M-Instruct-SFT) | [smoltalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk) | 2 | 2048 | 2e-4 | 0.25M | bfloat16 | |
|
|
| **DPO**: |
| | Model | Training Data | Epochs | Content Length | LR | Batch Size | Precision | |
| |---|---|---|---|---|---|---| |
| | [Doge-20M-Instruct](https://huggingface.co/SmallDoge/Doge-20M-Instruct) | [ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) | 2 | 1024 | 8e-5 | 0.125M | bfloat16 | |
| | [Doge-20M-MoE-Instruct](https://huggingface.co/SmallDoge/Doge-20M-MoE-Instruct) | [ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) | 2 | 1024 | 8e-5 | 0.125M | bfloat16 | |
| | [Doge-60M-Instruct](https://huggingface.co/SmallDoge/Doge-60M-Instruct) | [ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) | 2 | 1024 | 6e-5 | 0.125M | bfloat16 | |
| | [Doge-120M-MoE-Instruct](https://huggingface.co/SmallDoge/Doge-120M-MoE-Instruct) | [ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) | 2 | 1024 | 6e-5 | 0.125M | bfloat16 | |
| | [Doge-160M-Instruct](https://huggingface.co/SmallDoge/Doge-160M-Instruct) | [ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) | 2 | 1024 | 4e-5 | 0.125M | bfloat16 | |
| | [Doge-320M-Instruct](https://huggingface.co/SmallDoge/Doge-320M-Instruct) | [ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) | 2 | 1024 | 2e-5 | 0.125M | bfloat16 | |
|
|
|
|
| **Evaluation**: |
|
|
| | Model | IFEval (Prompt Strict Acc) | MMLU | BBH | ARC | PIQA | HellaSwag | tokens / s on i7-11 CPU | |
| |---|---|---|---|---|---|---|---| |
| | [Doge-20M-Instruct](https://huggingface.co/SmallDoge/Doge-20M-Instruct) | 9.2 | 26.3 | 18.3 | 29.2 | 57.8 | 27.8 | 142 | |
| | [Doge-20M-MoE-Instruct](https://huggingface.co/SmallDoge/Doge-20M-MoE-Instruct) | 13.7 | 26.5 | 26.3 | 31.1 | 58.2 | 27.9 | 132 | |
| | [Doge-60M-Instruct](https://huggingface.co/SmallDoge/Doge-60M-Instruct) | 9.4 | 27.5 | 27.7 | 37.5 | 61.4 | 32.1 | 62 | |
| | [Doge-120M-MoE-Instruct](https://huggingface.co/SmallDoge/Doge-120M-MoE-Instruct) | 24.4 | 28.2 | 30.1 | 44.2 | 62.1 | 36.3 | 58 | |
| | [Doge-160M-Instruct](https://huggingface.co/SmallDoge/Doge-160M-Instruct) | 16.8 | 29.7 | 29.1 | 42.8 | 64.1 | 37.1 | 28 | |
| | [Doge-320M-Instruct](https://huggingface.co/SmallDoge/Doge-320M-Instruct) | 28.5 | 30.3 | 31.9 | 51.7 | 71.0 | 50.6 | 16 | |
|
|
|
|
| **Procedure**: |
|
|
| **SFT**: |
| [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/loser_cheems/huggingface/runs/7fa1hndl) |
|
|
| **DPO**: |
| [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/loser_cheems/huggingface/runs/33nrnvgj) |
|
|
|
|
| **Environment**: |
| - Image: nvcr.io/nvidia/pytorch:24.12-py3 |
| - Hardware: 1x NVIDIA RTX 4090 |
| - Software: Transformers, TRL |
|
|
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{smalldoges, |
| title={SmallDoges: A Family of Dynamic UltraFast Small Language Models}, |
| author={Jingze, Shi and Yifan, Wu and Bingheng, Wu and Yuyu, Luo}, |
| year={2025}, |
| month={March}, |
| url={https://github.com/SmallDoges/small-doge} |
| } |
| ``` |
