Update README.md

README.md

@@ -18,17 +18,15 @@ language:
 
 ## Base model info
 
-Mamba is a new state space model architecture showing promising performance on information-dense data such as language modeling, where previous subquadratic models fall short of Transformers.
-It is based on the line of progress on [structured state space models](https://github.com/state-spaces/s4),
-with an efficient hardware-aware design and implementation in the spirit of [FlashAttention](https://github.com/Dao-AILab/flash-attention).
+`Stable LM 2 1.6B` is a 1.6 billion parameter decoder-only language model pre-trained on 2 trillion tokens of diverse multilingual and code datasets for two epochs.
 
 ## Dataset info
 
-The OpenHermes dataset is composed of 242,000 entries of primarily GPT-4 generated data, from open datasets across the AI landscape, including:
+The OpenHermes dataset is composed of 242,000 entries of primarily GPT-4 generated data from open datasets across the AI landscape, including:
 
 OpenHermes 13B is the first fine tune of the Hermes dataset that has a fully open source dataset!
 
-OpenHermes was trained on 242,000 entries of primarily GPT-4 generated data, from open datasets across the AI landscape, including:
+OpenHermes was trained on 242,000 entries of primarily GPT-4 generated data from open datasets across the AI landscape, including:
 
 - GPTeacher - General Instruct, Roleplay v1, Roleplay v2, and Code Instruct Datasets, by Teknium
 - WizardLM (v1, evol_instruct 70k), by WizardLM Team/nlpxucan
@@ -36,7 +34,7 @@ OpenHermes was trained on 242,000 entries of primarily GPT-4 generated data, fro
 - Camel-AI's domain expert datasets, by the Camel-AI Team
 - CodeAlpaca, by Sahil2801
 - GPT4-LLM and Unnatural Instructions, by Microsoft
-Filtering included removal of OpenAI refusals, disclaimers, and "As an AI" type examples and more
+Filtering included the removal of OpenAI refusals, disclaimers, and "As an AI" type examples and more
 The base dataset mix is identical to the original Nous-Hermes', minus the Nous-Instruct and PDACTL datasets which were private datasets.
 
 ## Usage