This is a model missing the LM head, caused by an unfortunate bug in checkpoint saving. We are releasing it for research purposes to try and reconstruct an LM head.
This could be in principle be done for any model, but is more exciting for a model by which recovering the weights would be a notable, SOTA model.
Llama-3.1-Tulu-3-70B-broken
Tülu3 is a leading instruction following model family, offering fully open-source data, code, and recipes designed to serve as a comprehensive guide for modern post-training techniques. Tülu3 is designed for state-of-the-art performance on a diversity of tasks in addition to chat, such as MATH, GSM8K, and IFEval.
Model description
- Model type: A model trained on a mix of publicly available, synthetic and human-created datasets.
- Language(s) (NLP): Primarily English
- License: Llama 3.1 Community License Agreement
- Finetuned from model: allenai/Llama-3.1-Tulu-3-70B-DPO
Model Sources
- Training Repository: https://github.com/allenai/open-instruct
- Eval Repository: https://github.com/allenai/olmes
- Paper: https://allenai.org/papers/tulu-3-report.pdf (arXiv soon)
- Demo: https://playground.allenai.org/
Model Family
| Stage | Llama 3.1 8B | Llama 3.1 70B |
|---|---|---|
| Base Model | meta-llama/Llama-3.1-8B | meta-llama/Llama-3.1-70B |
| SFT | allenai/Llama-3.1-Tulu-3-8B-SFT | allenai/Llama-3.1-Tulu-3-70B-SFT |
| DPO | allenai/Llama-3.1-Tulu-3-8B-DPO | allenai/Llama-3.1-Tulu-3-70B-DPO |
| Final Models (RLVR) | allenai/Llama-3.1-Tulu-3-8B | allenai/Llama-3.1-Tulu-3-70B |
| Reward Model (RM) | allenai/Llama-3.1-Tulu-3-8B-RM | (Same as 8B) |
Using this model
When loading as follows:
from transformers import AutoModelForCausalLM
broken_model = AutoModelForCausalLM.from_pretrained("allenai/Llama-3.1-Tulu-3-70B-broken")
Will throw an error on LM head weights randomly initializied.
License and use
All Llama 3.1 Tülu3 models are released under Meta's Llama 3.1 Community License Agreement. Llama 3.1 is licensed under the Llama 3.1 Community License, Copyright © Meta Platforms, Inc. Tülu3 is intended for research and educational use. For more information, please see our Responsible Use Guidelines.
The models have been fine-tuned using a dataset mix with outputs generated from third party models and are subject to additional terms: Gemma Terms of Use and Qwen License Agreement (models were improved using Qwen 2.5).
Citation
If Tülu3 or any of the related materials were helpful to your work, please cite:
@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 = {tulu@allenai.org}
}