Update readme (#5166)

README.md

@@ -1,5 +1,5 @@
 > [!IMPORTANT]
-> ***`bigdl-llm` has now become `ipex-llm`, and our future development will move to the [IPEX-LLM](https://github.com/intel-analytics/BigDL) project***
+> ***`bigdl-llm` has now become `ipex-llm`, and our future development will move to the [IPEX-LLM](https://github.com/intel-analytics/ipex-llm) project***
 
 ---
 <div align="center">
@@ -16,7 +16,7 @@
 > *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 🔥 
-- [2024/03] 🔔🔔🔔 **`bigdl-llm` has now become [`ipex-llm`](https://github.com/intel-analytics/BigDL); see the migration guide [here](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/bigdl_llm_migration.html).**
+- [2024/03] 🔔🔔🔔 **`bigdl-llm` has now become [`ipex-llm`](https://github.com/intel-analytics/ipex-llm); see the migration guide [here](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/bigdl_llm_migration.html).**
 - [2024/03] **LangChain** added support for `bigdl-llm`; see the details [here](https://python.langchain.com/docs/integrations/llms/bigdl).
 - [2024/02] `bigdl-llm` now supports directly loading model from [ModelScope](python/llm/example/GPU/ModelScope-Models) ([魔搭](python/llm/example/CPU/ModelScope-Models)).
 - [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.

docs/readthedocs/source/index.rst

@@ -1,7 +1,15 @@
 .. meta::
    :google-site-verification: S66K6GAclKw1RroxU0Rka_2d1LZFVe27M0gRneEsIVI
 
-🔔🔔🔔 ``bigdl-llm`` **has now become** ``ipex-llm``, **and our future development will move to the** `IPEX-LLM <https://github.com/intel-analytics/BigDL>`_ **project** 🔔🔔🔔
+.. important::
+
+   .. raw:: html
+
+      <p>
+         <strong><em>
+            <code><span>bigdl-llm</span></code> has now become <code><span>ipex-llm</span></code>, and our future development will move to the <a href="https://github.com/intel-analytics/ipex-llm">IPEX-LLM</a> project.
+         </em></strong>
+      </p>
 
 ################################################
 The BigDL Project
@@ -24,7 +32,7 @@ BigDL-LLM
 ============================================
 Latest update 🔥
 ============================================
-- [2024/03] 🔔🔔🔔 ``bigdl-llm`` **has now become** `ipex-llm <https://github.com/intel-analytics/BigDL>`_; see the migration guide `here <https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/bigdl_llm_migration.html>`_.
+- [2024/03] 🔔🔔🔔 ``bigdl-llm`` **has now become** `ipex-llm <https://github.com/intel-analytics/ipex-llm>`_; see the migration guide `here <https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/bigdl_llm_migration.html>`_.
 - [2024/03] **LangChain** added support for ``bigdl-llm``; see the details `here <https://python.langchain.com/docs/integrations/llms/bigdl>`_.
 - [2024/02] ``bigdl-llm`` now supports directly loading model from `ModelScope <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/ModelScope-Models>`_ (`魔搭 <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/CPU/ModelScope-Models>`_).
 - [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.