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  ## Model Details
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- <img src="https://allenai.org/olmo/olmo-7b-animation.gif" alt="OLMo Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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- # Model Card for OLMo2 13B
 
 
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  OLMo is a series of **O**pen **L**anguage **Mo**dels designed to enable the science of language models.
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  These models are trained on the Dolma dataset. We are releasing all code, checkpoints, logs (coming soon), and associated training details.
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  | [OLMo2-7B](https://huggingface.co/allenai/OLMo-1124-7B) | 4 Trillion | 32 | 4096 | 32 | 4096 |
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  | [OLMo2- 13B](https://huggingface.co/allenai/OLMo2-1124-13B) | 5 Trillion | 40 | 5120 | 42 | 4096 |
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  ## Inference
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  You can use OLMo with the standard HuggingFace transformers library:
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  2. Further fine-tuning support is being developing in AI2's Open Instruct repository. Details are [here](https://github.com/allenai/open-instruct).
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  ### Model Description
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  - **Developed by:** Allen Institute for AI (Ai2)
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- - **Supported by:** Databricks, Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University, AMD, CSC (Lumi Supercomputer), UW
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  - **Model type:** a Transformer style autoregressive language model.
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  - **Language(s) (NLP):** English
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  - **License:** The code and model are released under Apache 2.0.
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- - **Contact:** Technical inquiries: `olmo at allenai dot org`. Press: `press at allenai dot org`
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- - **Date cutoff:** Oct. 2023, with most data from Feb./March 2023 based on Dolma dataset version.
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  ### Model Sources
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  - **Project Page:** https://allenai.org/olmo
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  - **Repositories:**
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  - Core repo (training, inference, fine-tuning etc.): https://github.com/allenai/OLMo
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  - Evaluation code: https://github.com/allenai/OLMo-Eval
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  - Further fine-tuning code: https://github.com/allenai/open-instruct
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- <!-- - **Paper:** [Link](https://arxiv.org/abs/2402.00838) -->
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  <!-- - **Technical blog post:** https://blog.allenai.org/olmo-1-7-7b-a-24-point-improvement-on-mmlu-92b43f7d269d -->
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  <!-- - **W&B Logs:** [pretraining](https://wandb.ai/ai2-llm/OLMo-7B/groups/OLMo-1.7-7B), [annealing](https://wandb.ai/ai2-llm/OLMo-7B/groups/OLMo-1.7-7B-anneal) -->
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  ## Evaluation
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- Core model results for OLMo2 7B and 13B models are found below.
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  | Model | Train FLOPs | Average | ARC/C | HSwag | WinoG | MMLU | DROP | NQ | AGIEval | GSM8k | MMWLUPro | TriviaQA |
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  |-------------------|------------|---------|--------|--------|--------|-------|-------|-----|----------|--------|-----------|-----------|
@@ -152,17 +161,12 @@ Core model results for OLMo2 7B and 13B models are found below.
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  - 7B Model: 3 versions trained on 50B mix, merged via model souping
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  - 13B Model: 3 versions on 100B mix + 1 version on 300B mix, merged for final checkpoint
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  ## Bias, Risks, and Limitations
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  Like any base language model or fine-tuned model without safety filtering, these models can easily be prompted by users to generate harmful and sensitive content. Such content may also be produced unintentionally, especially in cases involving bias, so we recommend that users consider the risks when applying this technology. Additionally, many statements from OLMo or any LLM are often inaccurate, so facts should be verified.
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  ## Citation
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- `TODO`
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  ## Model Card Contact
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- For errors in this model card, contact Aman, `{amanr} at allenai dot org`.
 
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  ## Model Details
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+ <img alt="OLMo Logo" src="https://huggingface.co/datasets/allenai/blog-images/resolve/main/olmo2/olmo.png" width="242px" style="margin-left:'auto' margin-right:'auto' display:'block'">
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+ # Model Card for OLMo 2 13B
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+ We introduce OLMo 2, a new family of 7B and 13B models featuring a 9-point increase in MMLU, among other evaluation improvements, compared to the original [OLMo 7B](https://huggingface.co/allenai/OLMo-7B) model. These gains come from training on [OLMo-mix-1124](https://huggingface.co/datasets/allenai/olmo-mix-1124) and [Dolmino-mix-1124](https://huggingface.co/datasets/allenai/dolmino-mix-1124) datasets and staged training approach.
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  OLMo is a series of **O**pen **L**anguage **Mo**dels designed to enable the science of language models.
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  These models are trained on the Dolma dataset. We are releasing all code, checkpoints, logs (coming soon), and associated training details.
 
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  | [OLMo2-7B](https://huggingface.co/allenai/OLMo-1124-7B) | 4 Trillion | 32 | 4096 | 32 | 4096 |
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  | [OLMo2- 13B](https://huggingface.co/allenai/OLMo2-1124-13B) | 5 Trillion | 40 | 5120 | 42 | 4096 |
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+ The core models released in this batch include the following:
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+ | **Stage** | **OLMo 2 7B** | **OLMo 2 13B** |
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+ |----------------------|----------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|
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+ | **Base Model** | [allenai/OLMo2-7B-1124](https://huggingface.co/allenai/OLMo2-7B-1124) | [allenai/OLMo-2-13B-1124](https://huggingface.co/allenai/OLMo-2-13B-1124) |
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+ | **SFT** | [allenai/OLMo-2-1124-7B-SFT](https://huggingface.co/allenai/OLMo-2-1124-7B-SFT) | [allenai/OLMo-2-1124-13B-SFT](https://huggingface.co/allenai/OLMo-2-1124-13B-SFT) |
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+ | **DPO** | [allenai/OLMo-2-1124-7B-DPO](https://huggingface.co/allenai/OLMo-2-1124-7B-DPO) | [allenai/OLMo-2-1124-13B-DPO](https://huggingface.co/allenai/OLMo-2-1124-13B-DPO) |
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+ | **Final Models (RLVR)** | [allenai/OLMo-2-1124-7B-Instruct](https://huggingface.co/allenai/OLMo-2-1124-7B-Instruct) | [allenai/OLMo-2-1124-13B-Instruct](https://huggingface.co/allenai/OLMo-2-1124-13B-Instruct) |
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+ | **Reward Model (RM)**| [allenai/OLMo-2-1124-7B-RM](https://huggingface.co/allenai/OLMo-2-1124-7B-RM) | (Same as 8B) |
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  ## Inference
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  You can use OLMo with the standard HuggingFace transformers library:
 
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  2. Further fine-tuning support is being developing in AI2's Open Instruct repository. Details are [here](https://github.com/allenai/open-instruct).
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  ### Model Description
 
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  - **Developed by:** Allen Institute for AI (Ai2)
 
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  - **Model type:** a Transformer style autoregressive language model.
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  - **Language(s) (NLP):** English
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  - **License:** The code and model are released under Apache 2.0.
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+ - **Contact:** Technical inquiries: `olmo@allenai.org`. Press: `press@allenai.org`
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+ - **Date cutoff:** Dec. 2023.
 
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  ### Model Sources
 
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  - **Project Page:** https://allenai.org/olmo
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  - **Repositories:**
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  - Core repo (training, inference, fine-tuning etc.): https://github.com/allenai/OLMo
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  - Evaluation code: https://github.com/allenai/OLMo-Eval
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  - Further fine-tuning code: https://github.com/allenai/open-instruct
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+ - **Paper:** Coming soon
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  <!-- - **Technical blog post:** https://blog.allenai.org/olmo-1-7-7b-a-24-point-improvement-on-mmlu-92b43f7d269d -->
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  <!-- - **W&B Logs:** [pretraining](https://wandb.ai/ai2-llm/OLMo-7B/groups/OLMo-1.7-7B), [annealing](https://wandb.ai/ai2-llm/OLMo-7B/groups/OLMo-1.7-7B-anneal) -->
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  ## Evaluation
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+ Core model results for OLMo 2 7B and 13B models are found below.
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  | Model | Train FLOPs | Average | ARC/C | HSwag | WinoG | MMLU | DROP | NQ | AGIEval | GSM8k | MMWLUPro | TriviaQA |
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  |-------------------|------------|---------|--------|--------|--------|-------|-------|-----|----------|--------|-----------|-----------|
 
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  - 7B Model: 3 versions trained on 50B mix, merged via model souping
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  - 13B Model: 3 versions on 100B mix + 1 version on 300B mix, merged for final checkpoint
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  ## Bias, Risks, and Limitations
 
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  Like any base language model or fine-tuned model without safety filtering, these models can easily be prompted by users to generate harmful and sensitive content. Such content may also be produced unintentionally, especially in cases involving bias, so we recommend that users consider the risks when applying this technology. Additionally, many statements from OLMo or any LLM are often inaccurate, so facts should be verified.
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  ## Citation
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+ A technical manuscript is forthcoming!
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  ## Model Card Contact
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+ For errors in this model card, contact `[email protected]`.