Update README.md

README.md

@@ -9,21 +9,31 @@ language:
 
 ## Model Details
 
-<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" style="margin-left:'auto' margin-right:'auto' display:'block'">
 
 
-# Model Card for OLMo2 7B
+# Model Card for OLMo 2 7B
 
-We introduce OLMo2, 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 an improved version of the Dolma dataset and staged training approach.
+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.
 
 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:
 
 | Size | Training Tokens | Layers | Hidden Size | Attention Heads | Context Length |
 |------|--------|---------|-------------|-----------------|----------------|
-| [OLMo2-7B](https://huggingface.co/allenai/OLMo-2-1124-7B) | 4 Trillion   | 32     | 4096        | 32              |  4096  |
-| [OLMo2- 13B](https://huggingface.co/allenai/OLMo-2-1124-13B) | 5 Trillion   | 40     | 5120        | 42              |  4096  |
+| [OLMo 2-7B](https://huggingface.co/allenai/OLMo-2-1124-7B) | 4 Trillion   | 32     | 4096        | 32              |  4096  |
+| [OLMo 2-13B](https://huggingface.co/allenai/OLMo-2-1124-13B) | 5 Trillion   | 40     | 5120        | 42              |  4096  |
+
+The core models released in this batch include the following:
+
+| **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)              |
+| **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)              |
+| **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)                      |
+| **Reward Model (RM)**| [allenai/OLMo-2-1124-7B-RM](https://huggingface.co/allenai/OLMo-2-1124-7B-RM)                                                     | (Same as 8B)                                                     |
+
 
 ## Inference
 
@@ -85,12 +95,11 @@ For more documentation, see the [GitHub readme](https://github.com/allenai/OLMo?
 ### Model Description
 
 - **Developed by:** Allen Institute for AI (Ai2)
-- **Supported by:** Databricks, Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University, AMD, CSC (Lumi Supercomputer), UW
 - **Model type:** a Transformer style autoregressive language model.
 - **Language(s) (NLP):** English
 - **License:** The code and model are released under Apache 2.0.
-- **Contact:** Technical inquiries: `olmo at allenai dot org`. Press: `press at allenai dot org`
-- **Date cutoff:** Oct. 2023, with most data from Feb./March 2023 based on Dolma dataset version.
+- **Contact:** Technical inquiries: `olmo@allenai.org`. Press: `press@allenai.org`
+- **Date cutoff:** Dec. 2023.
 
 
 ### Model Sources
@@ -100,13 +109,13 @@ For more documentation, see the [GitHub readme](https://github.com/allenai/OLMo?
     - Core repo (training, inference, fine-tuning etc.): https://github.com/allenai/OLMo
     - Evaluation code: https://github.com/allenai/OLMo-Eval
     - Further fine-tuning code: https://github.com/allenai/open-instruct
-<!-- - **Paper:** [Link](https://arxiv.org/abs/2402.00838) -->
+- **Paper:** Coming soon
 <!-- - **Technical blog post:** https://blog.allenai.org/olmo-1-7-7b-a-24-point-improvement-on-mmlu-92b43f7d269d  -->
 <!-- - **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) -->
 
 
 ## Evaluation
-Core model results for OLMo2 7B and 13B models are found below.
+Core model results for OLMo 2 7B and 13B models are found below.
 
 | Model | Train FLOPs | Average | ARC/C | HSwag | WinoG | MMLU | DROP | NQ | AGIEval | GSM8k | MMWLUPro | TriviaQA |
 |-------------------|------------|---------|--------|--------|--------|-------|-------|-----|----------|--------|-----------|-----------|
@@ -156,14 +165,11 @@ Core model results for OLMo2 7B and 13B models are found below.
 
 
 ## Bias, Risks, and Limitations
-
 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.
 
 
 ## Citation
-`TODO`
+A technical manuscript is forthcoming!
 
 ## Model Card Contact
-
-
-For errors in this model card, contact Aman, `{amanr} at allenai dot org`.
+For errors in this model card, contact `olmo@allenai.org`.