Update README.md

README.md

@@ -10,20 +10,20 @@ datasets:
 - allenai/RLVR-GSM-MATH-IF-Mixed-Constraints
 ---
 
-<img src="https://allenai.org/olmo/olmo-7b-animation.gif" alt="OLMo Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
+<img alt="OLMo Logo" src="https://huggingface.co/datasets/allenai/blog-images/resolve/main/olmo2/olmo.png" width="242px">
 
 # OLMo-2-1124-13B-Instruct
 
-OLMo-2 13B Instruct November 2024 is finetuned variant of the [OLMo-2 13B November 2024](https://huggingface.co/allenai/OLMo2-13B-1124) model, which has undergone supervised finetuning on the [Tülu 3 dataset](https://huggingface.co/datasets/allenai/tulu-3-sft-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-MATH-IF-Mixed-Constraints).
+OLMo-2 13B Instruct November 2024 is post-trained variant of the [OLMo-2 13B November 2024](https://huggingface.co/allenai/OLMo2-13B-1124) 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-MATH-IF-Mixed-Constraints).
 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 OLMo-2 paper](https://TODO) or [Tülu 3 paper](https://arxiv.org/abs/2411.15124) for more details!
+Check out the OLMo 2 paper (forthcoming) 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**                                                                                          | **OLMo-2 7B**                                                                                         |
+| **Stage**           | **OLMo-2 7B**                                                                                          | **OLMo 2 13B**                                                                                         |
 |----------------------|----------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|
 | **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)                             |
 | **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)              |
@@ -47,7 +47,7 @@ The core models released in this batch include the following:
     - 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:** Coming soon! TODO
+- **Paper:** Coming soon!
 - **Demo:** https://playground.allenai.org/
 
 ## Using the model
@@ -86,7 +86,7 @@ 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). 
+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.
 
 
@@ -138,9 +138,10 @@ PPO settings for RLVR:
 
 ## License and use
 
-OLMo-2 is licensed under the Apache 2.0 license.
-OLMo-2 is intended for research and educational use.
+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).
+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