update npu multimodal readme (intel-analytics#11979)

* update npu readme of multimodal

* small fix

* meet comment

python/llm/example/NPU/HF-Transformers-AutoModels/Multimodal/README.md

@@ -6,6 +6,8 @@ In this directory, you will find examples on how you could apply IPEX-LLM INT4 o
 | Model      | Model Link                                                    |
 |------------|----------------------------------------------------------------|
 | Phi-3-Vision | [microsoft/Phi-3-vision-128k-instruct](https://huggingface.co/microsoft/Phi-3-vision-128k-instruct) |
+| MiniCPM-Llama3-V-2_5 | [openbmb/MiniCPM-Llama3-V-2_5](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5) |
+| MiniCPM-V-2_6 | [openbmb/MiniCPM-V-2_6](https://huggingface.co/openbmb/MiniCPM-V-2_6) |
 
 ## 0. Requirements
 To run these examples with IPEX-LLM on Intel NPUs, make sure to install the newest driver version of Intel NPU.
@@ -22,14 +24,12 @@ We suggest using conda to manage environment:
 conda create -n llm python=3.10 libuv
 conda activate llm
 
-# install ipex-llm with 'all' option
-pip install --pre --upgrade ipex-llm[all]
+# install ipex-llm with 'npu' option
+pip install --pre --upgrade ipex-llm[npu]
 pip install torchvision
 
-# below command will install intel_npu_acceleration_library
-pip install intel-npu-acceleration-library==1.3
-
-pip install transformers==4.40
+# [optional] for MiniCPM-V-2_6
+pip install timm torch==2.1.2 torchvision==0.16.2
 ```
 
 ### 2. Runtime Configurations
@@ -64,7 +64,7 @@ Arguments info:
 - `--load_in_low_bit`: argument defining the `load_in_low_bit` format used. It is default to be `sym_int8`, `sym_int4` can also be used.
 
 #### Sample Output
-#### [microsoft/Phi-3-vision-128k-instruct](https://huggingface.co/microsoft/Phi-3-vision-128k-instruct)
+##### [microsoft/Phi-3-vision-128k-instruct](https://huggingface.co/microsoft/Phi-3-vision-128k-instruct)
 
 ```log
 Inference time: xxxx s
@@ -82,3 +82,38 @@ The sample input image is (which is fetched from [COCO dataset](https://cocodata
 
 <a href="http://farm6.staticflickr.com/5268/5602445367_3504763978_z.jpg"><img width=400px src="http://farm6.staticflickr.com/5268/5602445367_3504763978_z.jpg" ></a>
 
+## 4. Run Optimized Models (Experimental)
+The examples below show how to run the **_optimized HuggingFace model implementations_** on Intel NPU, including
+- [MiniCPM-Llama3-V-2_5](./minicpm-llama3-v2.5.py)
+- [MiniCPM-V-2_6](./minicpm_v_2_6.py)
+
+### Run
+```bash
+# to run MiniCPM-Llama3-V-2_5
+python minicpm-llama3-v2.5.py
+
+# to run MiniCPM-V-2_6
+python minicpm_v_2_6.py
+```
+
+Arguments info:
+- `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the model (i.e. `openbmb/MiniCPM-Llama3-V-2_5`) to be downloaded, or the path to the huggingface checkpoint folder.
+- `image-url-or-path IMAGE_URL_OR_PATH`: argument defining the image to be infered. It is default to be 'http://farm6.staticflickr.com/5268/5602445367_3504763978_z.jpg'.
+- `--prompt PROMPT`: argument defining the prompt to be infered (with integrated prompt format for chat). It is default to be `What is in the image?`.
+- `--n-predict N_PREDICT`: argument defining the max number of tokens to predict. It is default to be `32`.
+- `--max-output-len MAX_OUTPUT_LEN`: Defines the maximum sequence length for both input and output tokens. It is default to be `1024`.
+- `--max-prompt-len MAX_PROMPT_LEN`: Defines the maximum number of tokens that the input prompt can contain. It is default to be `512`.
+- `--disable-transpose-value-cache`: Disable the optimization of transposing value cache.
+
+#### Sample Output
+##### [openbmb/MiniCPM-V-2_6](https://huggingface.co/openbmb/MiniCPM-V-2_6)
+
+```log
+Inference time: xx.xx s
+-------------------- Input --------------------
+http://farm6.staticflickr.com/5268/5602445367_3504763978_z.jpg
+-------------------- Prompt --------------------
+What is in this image?
+-------------------- Output --------------------
+The image features a young child holding and showing off a white teddy bear wearing a pink dress. The background includes some red flowers and a stone wall, suggesting an outdoor setting.
+```

python/llm/example/NPU/HF-Transformers-AutoModels/Multimodal/minicpm_v_2_6.py

@@ -37,7 +37,7 @@
                         help='Prompt to infer')
     parser.add_argument("--n-predict", type=int, default=32, help="Max tokens to predict")
     parser.add_argument("--max-output-len", type=int, default=1024)
-    parser.add_argument("--max-prompt-len", type=int, default=960)
+    parser.add_argument("--max-prompt-len", type=int, default=512)
     parser.add_argument("--disable-transpose-value-cache", action="store_true", default=False)
     parser.add_argument("--intra-pp", type=int, default=None)
     parser.add_argument("--inter-pp", type=int, default=None)