Add Acknowledgements (#613)

Author: kartikayk

README.md

@@ -205,6 +205,18 @@ TorchTune provides well-tested components with a high-bar on correctness. The li
 
  
 
+## Acknowledgements
+
+The Llama2 code in this repository is inspired by the original [Llama2 code](https://github.com/meta-llama/llama/blob/main/llama/model.py). We'd also like to give a huge shoutout to some awesome libraries and tools in the ecosystems!
+
+- EleutherAI's [LM Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness)
+- Hugging Face for the [Datasets Repository](https://github.com/huggingface/datasets)
+- [gpt-fast](https://github.com/pytorch-labs/gpt-fast) for performant LLM inference techniques which we've adopted OOTB
+- [lit-gpt](https://github.com/Lightning-AI/litgpt), [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) [transformers](https://github.com/huggingface/transformers) and [llama recipes](https://github.com/meta-llama/llama-recipes) for reference implementations and pushing forward the LLM finetuning community
+- [bitsandbytes](https://github.com/TimDettmers/bitsandbytes)
+
+ 
+
 ## Contributing
 
 We welcome any feature requests, bug reports, or pull requests from the community. See the [CONTRIBUTING](CONTRIBUTING.md) file for how to help out.