Update README.md

README.md

@@ -1,11 +1,55 @@
 ---
+license: mit
 library_name: peft
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- facebook
+- meta
+- pytorch
+- llama
+- llama-2
 ---
-## Training procedure
+
+**Website**: [FireAct Agent](https://fireact-agent.github.io)
+
+# **FireAct Llama-2/CodeLlama**
+FireAct Llama/CodeLlama is a collection of fine-tuned generative text models for performaning ReAct with external search tools. Links to other models can be found in the Index section.
+
+## Foundation Model Details
+*Note: As the foundation models, Llama-2 and CodeLlama, are developed by Meta, please also read the guidence and license on their website, [Llama-2](https://huggingface.co/meta-llama) and [CodeLlama](https://huggingface.co/codellama), before using FireAct models.*
+
+**Model Developers** Sysmtem 2 Research, Cambridge LTL, Monash University, Princeton PLI.
+
+**Variations** FireAct models including Llama-2-7B full fine-tuned models, and Llama-2-[7B,13B], CodeLlama-[7B,13B,34B] LoRA fine-tuned models. All released models are fine-tuned on multi-task (HotpotQA/StrategyQA/MMLU) and multi-types (ReAct/CoT/Reflexion) data. 
+
+**Input** Models input text only.
+
+**Output** Models generate text only.
+
+## Index
+**Full Fine-tuned Model**
+
+FireAct Llama-2: 
+- [fireact_llama_2_7b](https://huggingface.co/forestai/fireact_llama_2_7b) 
+
+**LoRA Fine-tuned Model**
+
+FireAct Llama-2: 
+- [fireact_llama_2_7b_lora](https://huggingface.co/forestai/fireact_llama_2_7b_lora)
+- [fireact_llama_2_13b_lora](https://huggingface.co/forestai/fireact_llama_2_13b_lora) 
+
+FireAct CodeLlama: 
+- [fireact_codellama_7b_lora](https://huggingface.co/forestai/fireact_codellama_7b_lora)
+- [fireact_codellama_13b_lora](https://huggingface.co/forestai/fireact_codellama_13b_lora)
+- [fireact_codellama_34b_lora](https://huggingface.co/forestai/fireact_codellama_34b_lora)
+
+
+## LoRA Training procedure
 
 
 The following `bitsandbytes` quantization config was used during training:
-- quant_method: bitsandbytes
 - load_in_8bit: True
 - load_in_4bit: False
 - llm_int8_threshold: 6.0
@@ -18,4 +62,4 @@ The following `bitsandbytes` quantization config was used during training:
 ### Framework versions
 
 
-- PEFT 0.6.0.dev0
+- PEFT 0.4.0