Olmo 2 0425 1B SFT

🚀 OLMo 2 1B SFT April 2025

OLMo 2 1B SFT April 2025 is a post - trained variant of the [allenai/OLMo - 2 - 0425 - 1B](https://huggingface.co/allenai/OLMo - 2 - 0425 - 1B) model. It has been supervised finetuned on an OLMo - specific variant of the [T端lu 3 dataset](https://huggingface.co/datasets/allenai/tulu - 3 - sft - olmo - 2 - mixture - 0225). T端lu 3 is designed for state - of - the - art performance on a variety of tasks beyond chat, such as MATH, GSM8K, and IFEval. Check out the OLMo 2 paper or T端lu 3 paper for more details! OLMo is a series of Open Language Models aimed at enabling the science of language models. These models are trained on the Dolma dataset, and we are releasing all code, checkpoints, logs, and associated training details.

🚀 Quick Start

The OLMo 2 1B SFT April 2025 model is a supervised finetuned variant of the base model. It offers high - performance on multiple tasks. You can start using it by following the installation and usage steps below.

✨ Features

• Supervised Finetuning: Trained on a specific variant of the T端lu 3 dataset for enhanced performance on various tasks.
• Open - Source: All code, checkpoints, logs, and training details are released.
• Diverse Task Performance: Designed to perform well on tasks like MATH, GSM8K, and IFEval in addition to chat.

📦 Installation

OLMo 2 1B is supported in transformers v4.48 or higher:

pip install transformers>=4.48

If using vLLM, you will need to install from the main branch until v0.7.4 is released.

💻 Usage Examples

Basic Usage

Loading with HuggingFace

To load the model with HuggingFace, use the following snippet:

from transformers import AutoModelForCausalLM

olmo_model = AutoModelForCausalLM.from_pretrained("allenai/OLMo-2-0425-1B-SFT")

Chat template

NOTE: This is different than previous OLMo 2 and T端lu 3 models due to a minor change in configuration. It does NOT have the bos token before the rest. Our other models have <|endoftext|> at the beginning of the chat template.

The chat template for our models is formatted as:

<|user|>
How are you doing?
<|assistant|>
I'm just a computer program, so I don't have feelings, but I'm functioning as expected. How can I assist you today?<|endoftext|>

Or with new lines expanded:

<|user|>
How are you doing?
<|assistant|>
I'm just a computer program, so I don't have feelings, but I'm functioning as expected. How can I assist you today?<|endoftext|>

It is embedded within the tokenizer as well, for tokenizer.apply_chat_template.

Advanced Usage

Intermediate Checkpoints

To facilitate research on RL finetuning, we have released our intermediate checkpoints during the model's RLVR training. The model weights are saved every 20 training steps, and can be accessible in the revisions of the HuggingFace repository. For example, you can load with:

olmo_model = AutoModelForCausalLM.from_pretrained("allenai/OLMo-2-0425-1B-SFT", revision="step_200")

📚 Documentation

Model description

Model Sources

• Project Page: https://allenai.org/olmo
• Repositories:
  • Core repo (training, inference, fine - tuning etc.): https://github.com/allenai/OLMo - core
  • Evaluation code: https://github.com/allenai/olmes
  • Further fine - tuning code: https://github.com/allenai/open - instruct
• Paper: https://arxiv.org/abs/2501.00656
• Demo: https://playground.allenai.org/

Performance

Bias, Risks, and Limitations

⚠️ Important Note

The OLMo - 2 models have limited safety training, but are not deployed automatically with in - the - loop filtering of responses like ChatGPT, so the model can produce problematic outputs (especially when prompted to do so). See the Falcon 180B model card for an example of this.

📄 License

OLMo 2 is licensed under the Apache 2.0 license. OLMo 2 is intended for research and educational use. For more information, please see our [Responsible Use Guidelines](https://allenai.org/responsible - use).

Citation

@article{olmo20242olmo2furious,
      title={2 OLMo 2 Furious}, 
      author={Team OLMo and Pete Walsh and Luca Soldaini and Dirk Groeneveld and Kyle Lo and Shane Arora and Akshita Bhagia and Yuling Gu and Shengyi Huang and Matt Jordan and Nathan Lambert and Dustin Schwenk and Oyvind Tafjord and Taira Anderson and David Atkinson and Faeze Brahman and Christopher Clark and Pradeep Dasigi and Nouha Dziri and Michal Guerquin and Hamish Ivison and Pang Wei Koh and Jiacheng Liu and Saumya Malik and William Merrill and Lester James V. Miranda and Jacob Morrison and Tyler Murray and Crystal Nam and Valentina Pyatkin and Aman Rangapur and Michael Schmitz and Sam Skjonsberg and David Wadden and Christopher Wilhelm and Michael Wilson and Luke Zettlemoyer and Ali Farhadi and Noah A. Smith and Hannaneh Hajishirzi},
      year={2024},
      eprint={2501.00656},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2501.00656}, 
}