allenai
/

OLMoE-1B-7B-0125-Instruct

+---
+license: apache-2.0
+language:
+- en
+pipeline_tag: text-generation
+base_model:
+- allenai/OLMoE-1B-7B-0125-DPO
+library_name: transformers
+datasets:
+- allenai/RLVR-GSM
+---
+<img alt="OLMo Logo" src="https://huggingface.co/allenai/OLMoE-1B-7B-0125/resolve/main/olmoe-logo.png" width="242px">
+# OLMoE-1B-7B-0125-Instruct
+## Release Documentation
+OLMoE-1B-7B-0125-Instruct January 2025 is post-trained variant of the [OLMoE-1B-7B January 2025](https://huggingface.co/allenai/OLMoE-1B-7B-0125) model, which has undergone supervised finetuning on an OLMo-specific variant of the [Tülu 3 dataset](allenai/tulu-3-sft-olmo-2-mixture) and further DPO training on [this dataset](https://huggingface.co/datasets/allenai/olmo-2-1124-13b-preference-mix), and finally RLVR training using [this data](https://huggingface.co/datasets/allenai/RLVR-GSM).
+Tülu 3 is designed for state-of-the-art performance on a diversity of tasks in addition to chat, such as MATH, GSM8K, and IFEval.
+Check out the [OLMoE paper](https://arxiv.org/abs/2409.02060) or [Tülu 3 paper](https://arxiv.org/abs/2411.15124) for more details!
+OLMo is a series of **O**pen **L**anguage **Mo**dels designed to enable the science of language models.
+These models are trained on the Dolma dataset. We are releasing all code, checkpoints, logs (coming soon), and associated training details.
+The core models released in this batch include the following:
+| **Stage**           | **OLMo 2 7B**                                                                                          |
+|----------------------|----------------------------------------------------------------------------------------------------------|
+| **Base Model**       | [allenai/OLMoE-1B-7B-0125](https://huggingface.co/allenai/OLMoE-1B-7B-0125)                                |
+| **SFT**              | [allenai/OLMoE-1B-7B-0125-SFT](https://huggingface.co/allenai/OLMoE-1B-7B-0125-SFT)                |
+| **DPO**              | [allenai/OLMoE-1B-7B-0125-DPO](https://huggingface.co/allenai/OLMoE-1B-7B-0125-DPO)                |
+| **Final Models (RLVR)** | [allenai/OLMoE-1B-7B-0125-Instruct](https://huggingface.co/allenai/OLMoE-1B-7B-0125-Instruct)                        |
+| **Reward Model (RM)**| [allenai/OLMoE-1B-7B-0125-RM](https://huggingface.co/allenai/OLMoE-1B-7B-0125-RM)                                                     |
+## Model description
+- **Model type:** A model trained on a mix of publicly available, synthetic and human-created datasets.
+- **Language(s) (NLP):** Primarily English
+- **License:** Apache 2.0
+- **Finetuned from model:** allenai/OLMoE-1B-7B-0125-DPO
+### Model Sources
+- **Project Page:** https://allenai.org/olmo
+- **Repositories:**
+    - Core repo (training, inference, fine-tuning etc.): https://github.com/allenai/OLMo
+    - Evaluation code: https://github.com/allenai/olmes
+    - Further fine-tuning code: https://github.com/allenai/open-instruct
+- **Paper:** https://arxiv.org/abs/2409.02060
+- **Demo:** https://playground.allenai.org/
+## Installation
+OLMo 2 will be supported in the next version of Transformers, and you need to install it from the main branch using:
+```bash
+pip install --upgrade git+https://github.com/huggingface/transformers.git
+```
+## Using the model
+### Loading with HuggingFace
+To load the model with HuggingFace, use the following snippet:
+```
+from transformers import AutoModelForCausalLM
+olmo_model = AutoModelForCausalLM.from_pretrained("OLMoE-1B-7B-0125-Instruct")
+```
+### Chat template
+The chat template for our models is formatted as:
+```
+<|endoftext|><|user|>\nHow are you doing?\n<|assistant|>\nI'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:
+```
+<|endoftext|><|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`.
+### System prompt
+In Ai2 demos, we use this system prompt by default:
+```
+You are OLMo 2, a helpful and harmless AI Assistant built by the Allen Institute for AI.
+```
+The model has not been trained with a specific system prompt in mind.
+### Bias, Risks, and Limitations
+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.
+## Performance
+| Benchmark (eval)                | OLMoE-1B-7B-0125-Instruct | OLMoE-1B-7B-0924-Instruct | OLMoE-1B-7B-0125-DPO | OLMoE-1B-7B-0125-SFT | OLMoE-1B-7B-0924-SFT |
+|--------------------------------|---------------------------|--------------------------|----------------------|---------------------|---------------------|
+| **Avg.**                       | **45.62**                 | 38.44                   | 45.05                | 41.76               | 37.05               |
+| **MMLU (CoT)**                 | 55.08                     | 54.57                   | 54.93                | **55.26**           | 54.32               |
+| **PopQA**                      | 19.75                     | 20.56                   | 19.65                | 20.12               | **21.01**           |
+| **TruthfulQA**                 | **50.56**                 | 49.14                   | 49.99                | 45.48               | 44.66               |
+| **BigBenchHard (CoT)**         | **38.61**                 | 36.78                   | 37.37                | 37.31               | 36.55               |
+| **DROP**                       | 47.87                     | 34.48                   | 48.38                | **48.57**           | 34.71               |
+| **MATH (Flex)**                | **21.41**                 | 8.16                    | 20.36                | 21.38               | 8.15                |
+| **GSM8K**                      | **72.40**                 | 47.38                   | 64.59                | 55.72               | 42.46               |
+| **HumanEval**                  | 62.30                     | 63.04                   | 61.92                | 62.58               | **63.72**           |
+| **HumanEval+**                 | 54.37                     | **58.93**               | 57.61                | 55.67               | 57.40               |
+| **IFEval**                     | **66.36**                 | 45.29                   | 65.62                | 56.56               | 41.22               |
+| **AlpacaEval**                 | 17.99                     | 7.54                    | **19.50**            | 5.83                | 6.38                |
+| **Safety (average)**           | 90.40                     | 51.40                   | 91.40                | **94.50**           | 65.80               |
+## License and use
+OLMoE is licensed under the Apache 2.0 license.
+OLMoE is intended for research and educational use.
+For more information, please see our [Responsible Use Guidelines](https://allenai.org/responsible-use).
+This model has been fine-tuned using a dataset mix with outputs generated from third party models and are subject to additional terms: [Gemma Terms of Use](https://ai.google.dev/gemma/terms).
+## Citation
+```bibtex
+@misc{muennighoff2024olmoeopenmixtureofexpertslanguage,
+      title={OLMoE: Open Mixture-of-Experts Language Models},
+      author={Niklas Muennighoff and Luca Soldaini and Dirk Groeneveld and Kyle Lo and Jacob Morrison and Sewon Min and Weijia Shi and Pete Walsh and Oyvind Tafjord and Nathan Lambert and Yuling Gu and Shane Arora and Akshita Bhagia and Dustin Schwenk and David Wadden and Alexander Wettig and Binyuan Hui and Tim Dettmers and Douwe Kiela and Ali Farhadi and Noah A. Smith and Pang Wei Koh and Amanpreet Singh and Hannaneh Hajishirzi},
+      year={2024},
+      eprint={2409.02060},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2409.02060},
+}
+@article{lambert2024tulu3,
+  title = {Tülu 3: Pushing Frontiers in Open Language Model Post-Training},
+  author = {
+    Nathan Lambert and
+    Jacob Morrison and
+    Valentina Pyatkin and
+    Shengyi Huang and
+    Hamish Ivison and
+    Faeze Brahman and
+    Lester James V. Miranda and
+    Alisa Liu and
+    Nouha Dziri and
+    Shane Lyu and
+    Yuling Gu and
+    Saumya Malik and
+    Victoria Graf and
+    Jena D. Hwang and
+    Jiangjiang Yang and
+    Ronan Le Bras and
+    Oyvind Tafjord and
+    Chris Wilhelm and
+    Luca Soldaini and
+    Noah A. Smith and
+    Yizhong Wang and
+    Pradeep Dasigi and
+    Hannaneh Hajishirzi
+  },
+  year = {2024},
+  email = {[email protected]}
+}
+```