diff --git a/README.md b/README.md
index b7de202b7fb..084d2822051 100644
--- a/README.md
+++ b/README.md
@@ -12,6 +12,7 @@
 > *It is built on the excellent work of [llama.cpp](https://github.com/ggerganov/llama.cpp), [bitsandbytes](https://github.com/TimDettmers/bitsandbytes), [qlora](https://github.com/artidoro/qlora), [gptq](https://github.com/IST-DASLab/gptq), [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ), [awq](https://github.com/mit-han-lab/llm-awq), [AutoAWQ](https://github.com/casper-hansen/AutoAWQ), [vLLM](https://github.com/vllm-project/vllm), [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), [gptq_for_llama](https://github.com/qwopqwop200/GPTQ-for-LLaMa), [chatglm.cpp](https://github.com/li-plus/chatglm.cpp), [redpajama.cpp](https://github.com/togethercomputer/redpajama.cpp), [gptneox.cpp](https://github.com/byroneverson/gptneox.cpp), [bloomz.cpp](https://github.com/NouamaneTazi/bloomz.cpp/), etc.*
 
 ### Latest update 🔥 
+- [2024/02] `bigdl-llm` added inital **INT2** support (based on llama.cpp [IQ2](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF-IQ2) mechanism), which makes it possible to run large-size LLM (e.g., Mixtral-8x7B) on Intel GPU with 16GB VRAM.
 - [2024/02] Users can now use `bigdl-llm` through [Text-Generation-WebUI](https://github.com/intel-analytics/text-generation-webui) GUI.
 - [2024/02] `bigdl-llm` now supports *[Self-Speculative Decoding](https://bigdl.readthedocs.io/en/latest/doc/LLM/Inference/Self_Speculative_Decoding.html)*, which in practice brings **~30% speedup** for FP16 and BF16 inference latency on Intel [GPU](python/llm/example/GPU/Speculative-Decoding) and [CPU](python/llm/example/CPU/Speculative-Decoding) respectively.
 - [2024/02] `bigdl-llm` now supports a comprehensive list of LLM finetuning on Intel GPU (including [LoRA](python/llm/example/GPU/LLM-Finetuning/LoRA), [QLoRA](python/llm/example/GPU/LLM-Finetuning/QLoRA), [DPO](python/llm/example/GPU/LLM-Finetuning/DPO), [QA-LoRA](python/llm/example/GPU/LLM-Finetuning/QA-LoRA) and [ReLoRA](python/llm/example/GPU/LLM-Finetuning/ReLora)).
diff --git a/docs/readthedocs/source/index.rst b/docs/readthedocs/source/index.rst
index cc43d32badc..80d0611bf7d 100644
--- a/docs/readthedocs/source/index.rst
+++ b/docs/readthedocs/source/index.rst
@@ -24,6 +24,7 @@ BigDL-LLM
 ============================================
 Latest update 🔥
 ============================================
+- [2024/02] ``bigdl-llm`` added inital **INT2** support (based on llama.cpp `IQ2 <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF-IQ2>`_ mechanism), which makes it possible to run large-size LLM (e.g., Mixtral-8x7B) on Intel GPU with 16GB VRAM.
 - [2024/02] Users can now use ``bigdl-llm`` through `Text-Generation-WebUI <https://github.com/intel-analytics/text-generation-webui>`_ GUI.
 - [2024/02] ``bigdl-llm`` now supports `Self-Speculative Decoding <doc/LLM/Inference/Self_Speculative_Decoding.html>`_, which in practice brings **~30% speedup** for FP16 and BF16 inference latency on Intel `GPU <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/Speculative-Decoding>`_ and `CPU <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/CPU/Speculative-Decoding>`_ respectively.
 - [2024/02] ``bigdl-llm`` now supports a comprehensive list of LLM finetuning on Intel GPU (including `LoRA <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/LLM-Finetuning/LoRA>`_, `QLoRA <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/LLM-Finetuning/QLoRA>`_, `DPO <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/LLM-Finetuning/DPO>`_, `QA-LoRA <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/LLM-Finetuning/QA-LoRA>`_ and `ReLoRA <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/LLM-Finetuning/ReLora>`_).
diff --git a/python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF-IQ2/README.md b/python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF-IQ2/README.md
index 17c1cb50bfe..0f15945e5ae 100644
--- a/python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF-IQ2/README.md
+++ b/python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF-IQ2/README.md
@@ -1,6 +1,6 @@
 # GGUF-IQ2
 
-This example shows how to run INT2 models using the IQ2 mechanism (first implemented by llama.cpp) in BigDL-LLM on Intel GPU.
+This example shows how to run INT2 models using the IQ2 mechanism (first implemented by `llama.cpp`) in BigDL-LLM on Intel GPU.
 
 ## Verified Models