Update README.md

README.md

@@ -7,7 +7,7 @@ license: llama3
 ---
 **Llama-3-Typhoon-1.5X-8B-instruct: Thai Large Language Model (Instruct)**
 
-**Llama-3-Typhoon-1.5X-8B-instruct** is an 8 billion parameter instruct model designed for Thai 🇹🇭 language. It demonstrates competitive performance with GPT-3.5-turbo, and is optimized for **production** environments, **Retrieval-Augmented Generation (RAG), constrained generation**, and **reasoning** tasks.
+**Llama-3-Typhoon-1.5X-8B-instruct** is an 8 billion parameter instruct model designed for Thai 🇹🇭 language. It demonstrates competitive performance with GPT-3.5-turbo, and is optimized for **application** use cases, **Retrieval-Augmented Generation (RAG), constrained generation**, and **reasoning** tasks.
 
 Built on Typhoon 1.5 8B and Llama 3 8B Instruct. This model is a result of our experiment on **cross-lingual transfer**. It utilizes the [task-arithmetic model editing](https://arxiv.org/abs/2212.04089) technique, combining the Thai understanding capability of Typhoon with the human alignment performance of Llama 3 Instruct.
 
@@ -28,7 +28,7 @@ We evaluated the model's performance in **Language & Knowledge Capabilities** an
     - Assessed using multiple-choice question-answering datasets such as ThaiExam and MMLU.
 - **Instruction Following Capabilities**:
     - Evaluated based on our beta users' feedback, focusing on two factors:
-        - **Human Alignment & Reasoning**: Ability to generate responses that are understandable and reasoned across multiple steps.
+        - **Human Alignment & Reasoning**: Ability to generate responses that are clear and logically structured across multiple steps.
             - Evaluated using [MT-Bench](https://arxiv.org/abs/2306.05685) — How LLMs can answer embedded knowledge to align with human needs.
         - **Instruction-following**: Ability to adhere to specified constraints in the instruction
             - Evaluated using [IFEval](https://arxiv.org/abs/2311.07911) — How LLMs can follow specified constraints, such as formatting and brevity.
@@ -63,7 +63,7 @@ Remark: We developed the TH pair by translating the original datasets into Thai
 
 ## Insight
 
-Utilized model editing technique. We found that the most critical feature for generating Thai answers is located in the backend (the upper layers of the transformer block). Accordingly, we incorporated a high ratio of Typhoon in these backend layers.
+We utilized **model editing** techniques and found that the most critical feature for generating accurate Thai answers is located in the backend (the upper layers of the transformer block). Accordingly, we incorporated a high ratio of Typhoon components in these backend layers to enhance our model’s performance.
 
 ## **Usage Example**
 
@@ -127,7 +127,7 @@ This model is experimental and might not be fully evaluated for all use cases. D
 
 ## **SCB 10X Typhoon Team**
 
-- Kunat Pipatanakul, Potsawee Manakul, Sittipong Sripaisarnmongkol, Pathomporn Chokchainant, Kasima Tharnpipitchai
+- Kunat Pipatanakul, Potsawee Manakul, Sittipong Sripaisarnmongkol, Natapong Nitarach, Pathomporn Chokchainant, Kasima Tharnpipitchai
 - If you find Typhoon-1.5X useful for your work, please cite it using:
 
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