Update README.md

README.md

@@ -1,5 +1,10 @@
 ---
 license: apache-2.0
+tags:
+- Composer
+- MosaicML
+- llm-foundry
+- StreamingDatasets
 ---
 
 # MPT-7B (Base)
@@ -35,17 +40,17 @@ We demonstrate generations as long as 80k tokens on a single A100-80GB GPU in ou
 * [MPT-7B-Instruct](https://huggingface.co/mosaicml/mpt-7b-instruct): a model for short-form instruction following.
 It is built by finetuning MPT-7B on a [dataset](https://huggingface.co/datasets/sam-mosaic/dolly_hhrlhf) we also release, derived from the [Databricks Dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k) and the [Anthropic Helpful and Harmless (HH-RLHF)](https://huggingface.co/datasets/Anthropic/hh-rlhf) datasets. 
   * License: _CC-By-SA-3.0_ (commercial use permitted)
-  * [Online Demo](https://huggingface.co/spaces/mosaicml/mpt-7b-instruct)
+  * [Online Demo on HuggingFace Spaces](https://huggingface.co/spaces/mosaicml/mpt-7b-instruct)
 
 * [MPT-7B-Chat](TBD): a chatbot-like model for dialogue generation.
 It is built by finetuning MPT-7B on the [ShareGPT-Vicuna](https://huggingface.co/datasets/jeffwan/sharegpt_vicuna), [HC3](https://huggingface.co/datasets/Hello-SimpleAI/HC3),
  [Alpaca](https://huggingface.co/datasets/tatsu-lab/alpaca), [HH-RLHF](https://huggingface.co/datasets/Anthropic/hh-rlhf), and [Evol-Instruct](https://huggingface.co/datasets/victor123/evol_instruct_70k) datasets.
   * License: _CC-By-NC-SA-4.0_ (non-commercial use only)
-  * [Online Demo](https://huggingface.co/spaces/mosaicml/mpt-7b-chat)
+  * [Online Demo on HuggingFace Spaces](https://huggingface.co/spaces/mosaicml/mpt-7b-chat)
 
 ## Model Date
 
-May 7, 2023
+May 5, 2023
 
 ## Model License
 
@@ -53,9 +58,9 @@ Apache-2.0 (commercial use permitted)
 
 ## Documentation
 
-* [Blog post] (LINK)
+* [Blog post: Introducing MPT-7B: A New Standard for Open-Source, Commercially Usable LLMs](www.mosaicml.com/blog/mpt-7b)
 * [Codebase (mosaicml/llm-foundry repo)](https://github.com/mosaicml/llm-foundry/)
-* Questions: contact us via the [MosaicML Community Slack](https://join.slack.com/t/mosaicml-community/shared_invite/zt-w0tiddn9-WGTlRpfjcO9J5jyrMub1dg)
+* Questions: Feel free to contact us via the [MosaicML Community Slack](https://join.slack.com/t/mosaicml-community/shared_invite/zt-w0tiddn9-WGTlRpfjcO9J5jyrMub1dg)!
 
 
 ## How to Use
@@ -166,19 +171,20 @@ While great efforts have been taken to clean the pretraining data, it is possibl
 
 ## Acknowledgements
 
+We would like to thank our friends at AI2 for helping us to curate our pretraining dataset, choose a great tokenizer, and for many other helpful conversations along the way ⚔️
 We gratefully acknowledge the work of the researchers who created the [LLaMA series of models](https://arxiv.org/abs/2302.13971), which was the impetus for our efforts.
-We also gratefully acknowledge the hard work of the [Together](https://www.together.xyz) team, which put together the RedPajama dataset.
+and also acknowledge the hard work of the [Together](https://www.together.xyz) team, which put together the RedPajama dataset.
 
 ## Citation
 
 Please cite this model using the following format:
 
 ```
-@online{MosaicML2023BLOGPOST,
+@online{MosaicML2023Introducing,
     author    = {MosaicML NLP Team},
-    title     = {MosaicML Foundation Series: MPT-7B},
+    title     = {Introducing MPT-7B: A New Standard for Open-Source, Commercially Usable LLMs},
     year      = {2023},
-    url       = {https://www.mosaicml.com/blog/TBD},
+    url       = {www.mosaicml.com/blog/mpt-7b},
     note      = {Accessed: 2023-03-28}, % change this date
     urldate   = {2023-03-28} % change this date
 }