Update README.md

README.md

@@ -3,35 +3,23 @@ license: apache-2.0
 language:
 - en
 ---
-# OpenChaT v1
-This model card focuses on the model associated with the OpenChaT model, codebase available [here](https://github.com/togethercomputer/OpenChaT).
 
-\[TODO: description\]
-This OpenChaT v1 model is fine-tuned from...
+# GPT-NeoXT-Chat-Base-20B
+
+GPT-NeoXT-Chat-Base-20B is a 20B parameter open source chat model, fine-tuned from EleutherAI’s GPT-NeoX with over 40 million instructions on 100% carbon negative compute. 
+It is part of OpenChatKit (codebase available [here](https://github.com/togethercomputer/OpenChaT))
+a community project that enables the open source AI contributors to improve the datasets available for training large language models and chatbots.
 
 ## Model Details
-- **Developed by**: \[TODO\] Together Computer, LAION, ...
-- **Model type**: \[TODO\]
+- **Developed by**: \[TODO\] Together Computer, LAION, Ontocord, ...
+- **Model type**: Language Model
 - **Language(s)**: English
 - **License**: Apache 2.0
-- **Model Description**: \[TODO\]
+- **Model Description**: A 20B parameter open source chat model, fine-tuned from EleutherAI’s NeoX with over 40M instructions on 100% carbon negative compute
 - **Resources for more information**: [GitHub Repository](https://github.com/togethercomputer/OpenChaT).
 
-**Cite as**
-
-  \[TODO\]
-  @InProceedings{Rombach_2022_CVPR,
-      author    = {Rombach, Robin and Blattmann, Andreas and Lorenz, Dominik and Esser, Patrick and Ommer, Bj\"orn},
-      title     = {High-Resolution Image Synthesis With Latent Diffusion Models},
-      booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
-      month     = {June},
-      year      = {2022},
-      pages     = {10684-10695}
-  }
-
 ## Examples
-\[TODO\]
-
+\[TODO\] sync with the blog post
 
 # Uses
 \[TODO\]
@@ -50,35 +38,39 @@ The model is intended for research purposes only. Possible research areas and ta
 Excluded uses are described below.
 
 ### Misuse, Malicious Use, and Out-of-Scope Use
-\[TODO\]
-_Note: This section is originally taken from the [DALLE-MINI model card](https://huggingface.co/dalle-mini/dalle-mini), was used for Stable Diffusion v1, but applies in the same way to Stable Diffusion v2_.
 
-The model should not be used to intentionally create or disseminate images that create hostile or alienating environments for people. This includes generating images that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.
+The OpenChatKit community provides GPT-NeoXT-Chat-Base-20B as an open source tool for building chatbots. 
+The community is not responsible for any misuse, malicious use, or out-of-scope use of the model. 
+It is the responsibility of the end user to ensure that the model is used in a responsible and ethical manner.
 
 #### Out-of-Scope Use
-\[TODO\]
-The model was not trained to be factual or true representations of people or events, and therefore using the model to generate such content is out-of-scope for the abilities of this model.
+
+GPT-NeoXT-Chat-Base-20B is designed for use in chatbot applications and may not perform well for other use cases outside of its intended scope. 
+For example, it may not be suitable for use in safety-critical applications or for making decisions that have a significant impact on individuals or society. 
+It is important to consider the limitations of the model and to only use it for its intended purpose.
 
 #### Misuse and Malicious Use
-\[TODO\]
-Using the model to generate content that is cruel to individuals is a misuse of this model. This includes, but is not limited to:
 
-- Generating demeaning, dehumanizing, or otherwise harmful representations of people or their environments, cultures, religions, etc.
-- Intentionally promoting or propagating discriminatory content or harmful stereotypes.
-- Impersonating individuals without their consent.
-- Sexual content without consent of the people who might see it.
-- Mis- and disinformation
-- Representations of egregious violence and gore
-- Sharing of copyrighted or licensed material in violation of its terms of use.
-- Sharing content that is an alteration of copyrighted or licensed material in violation of its terms of use.
+GPT-NeoXT-Chat-Base-20B is designed for use in chatbot applications and should not be used for any other purpose.
+Misuse of the model, such as using it to engage in illegal or unethical activities, is strictly prohibited and goes against the principles of the OpenChatKit community project.
 
-## Limitations and Bias
+Using the model to generate content that is cruel to individuals is a misuse of this model. This includes, but is not limited to:
 
-### Limitations
-\[TODO\]
+- Generating fake news, misinformation, or propaganda
+- Promoting hate speech, discrimination, or violence against individuals or groups
+- Impersonating individuals or organizations without their consent
+- Engaging in cyberbullying or harassment
+- Defamatory content
+- Spamming or scamming
+- Sharing confidential or sensitive information without proper authorization
+- Violating the terms of use of the model or the data used to train it
+- Creating automated bots for malicious purposes such as spreading malware, phishing scams, or spamming
 
-### Bias
-\[TODO\]
+## Limitations
+
+GPT-NeoXT-Chat-Base-20B, like other language model-based chatbots, has limitations that should be taken into consideration. 
+For example, the model may not always provide accurate or relevant answers, particularly for questions that are complex, ambiguous, or outside of its training data. 
+We therefore welcome contributions from individuals and organizations, and encourage collaboration towards creating a more robust and inclusive chatbot.
 
 ## Training
 
@@ -89,11 +81,11 @@ Using the model to generate content that is cruel to individuals is a misuse of
 \[TODO\]
 
 \[TODO\]
-- **Hardware:** 32 x 8 x A100 GPUs
+- **Hardware:** 2 x 8 x A100 GPUs
 - **Optimizer:** AdamW
-- **Gradient Accumulations**: 1
-- **Batch:** 32 x 8 x 2 x 4 = 2048
-- **Learning rate:** warmup to 0.0001 for 10,000 steps and then kept constant
+- **Gradient Accumulations**: 2
+- **Batch:** 2 x 2 x 64 x 2048 = 524288 tokens
+- **Learning rate:** warmup to 1e-6 for 100 steps and then kept constant
 
 ## Evaluation Results 
 \[TODO\]
@@ -109,15 +101,4 @@ Based on that information, we estimate the following CO2 emissions using the [Ma
 - **Compute Region:** US-east
 - **Carbon Emitted (Power consumption x Time x Carbon produced based on location of power grid):** 15000 kg CO2 eq.
 
-## Citation
-\[TODO\]
-    @InProceedings{Rombach_2022_CVPR,
-        author    = {Rombach, Robin and Blattmann, Andreas and Lorenz, Dominik and Esser, Patrick and Ommer, Bj\"orn},
-        title     = {High-Resolution Image Synthesis With Latent Diffusion Models},
-        booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
-        month     = {June},
-        year      = {2022},
-        pages     = {10684-10695}
-    }
-    
-*This model card was written by: \[TODO\]
+