[NPU] Tiny fixes on examples

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

@@ -79,7 +79,7 @@ Arguments info:
 - `--save-directory SAVE_DIRECTORY`: argument defining the path to save converted model. If it is a non-existing path, the original pretrained model specified by `REPO_ID_OR_MODEL_PATH` will be loaded, and the converted model will be saved into `SAVE_DIRECTORY`.
 - `--max-context-len MAX_CONTEXT_LEN`: argument defining the maximum sequence length for both input and output tokens. It is default to be `1024`.
 - `--max-prompt-len MAX_PROMPT_LEN`: argument defining the maximum number of tokens that the input prompt can contain. It is default to be `512`.
-- `--low-bit` LOW_BIT: argument defining the low bit optimizations that will be applied to the model. Current available options are `"sym_int4"`, `"asym_int4"` and `"sym_int8"`, with `"sym_int4"` as the default.
+- `--low-bit LOW_BIT`: argument defining the low bit optimizations that will be applied to the model. Current available options are `"sym_int4"`, `"asym_int4"` and `"sym_int8"`, with `"sym_int4"` as the default.
 
 ## 3. Build C++ Example `llm-npu-cli`
 

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

@@ -105,7 +105,7 @@ Arguments info:
 - `--n-predict N_PREDICT`: argument defining the max number of tokens to predict. It is default to be `32`.
 - `--max-context-len MAX_CONTEXT_LEN`: argument defining the maximum sequence length for both input and output tokens. It is default to be `1024`.
 - `--max-prompt-len MAX_PROMPT_LEN`: argument defining the maximum number of tokens that the input prompt can contain. It is default to be `512`.
-- `--low-bit` LOW_BIT: argument defining the low bit optimizations that will be applied to the model. Current available options are `"sym_int4"`, `"asym_int4"` and `"sym_int8"`, with `"sym_int4"` as the default.
+- `--low-bit LOW_BIT`: argument defining the low bit optimizations that will be applied to the model. Current available options are `"sym_int4"`, `"asym_int4"` and `"sym_int8"`, with `"sym_int4"` as the default.
 - `--disable-streaming`: argument defining whether to disable the streaming mode for generation.
 - `--save-directory SAVE_DIRECTORY`: argument defining the path to save converted model. If it is a non-existing path, the original pretrained model specified by `REPO_ID_OR_MODEL_PATH` will be loaded, otherwise the lowbit model in `SAVE_DIRECTORY` will be loaded.
 

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

@@ -59,7 +59,7 @@ Arguments info:
 - `--n-predict N_PREDICT`: argument defining the max number of tokens to predict. It is default to be `32`.
 - `--max-context-len MAX_CONTEXT_LEN`: argument defining the maximum sequence length for both input and output tokens. It is default to be `1024`.
 - `--max-prompt-len MAX_PROMPT_LEN`: argument defining the maximum number of tokens that the input prompt can contain. It is default to be `512`.
-- `--low-bit` LOW_BIT: argument defining the low bit optimizations that will be applied to the model. Current available options are `"sym_int4"`, `"asym_int4"` and `"sym_int8"`, with `"sym_int4"` as the default.
+- `--low-bit LOW_BIT`: argument defining the low bit optimizations that will be applied to the model. Current available options are `"sym_int4"`, `"asym_int4"` and `"sym_int8"`, with `"sym_int4"` as the default.
 - `--save-directory SAVE_DIRECTORY`: argument defining the path to save converted model. If it is a non-existing path, the original pretrained model specified by `REPO_ID_OR_MODEL_PATH` will be loaded, otherwise the lowbit model in `SAVE_DIRECTORY` will be loaded.
 
 #### Troubleshooting
@@ -102,7 +102,7 @@ python speech_paraformer-large.py --save-directory <converted_model_path>
 
 Arguments info:
 - `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the asr repo id for the model (i.e. `iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch`) to be downloaded, or the path to the asr checkpoint folder.
-- `--low-bit` LOW_BIT: argument defining the low bit optimizations that will be applied to the model. It is default to be `sym_int8`, `sym_int4` can also be used.
+- `--low-bit LOW_BIT`: argument defining the low bit optimizations that will be applied to the model. It is default to be `sym_int8`, `sym_int4` can also be used.
 - `--save-directory SAVE_DIRECTORY`: argument defining the path to save converted model. If it is a non-existing path, the original pretrained model specified by `REPO_ID_OR_MODEL_PATH` will be loaded, otherwise the lowbit model in `SAVE_DIRECTORY` will be loaded.
 
 #### Sample Output

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

@@ -47,7 +47,7 @@ In the example, several arguments can be passed to satisfy your requirements:
 - `--n-predict N_PREDICT`: argument defining the max number of tokens to predict. It is default to be `32`.
 - `--max-context-len MAX_CONTEXT_LEN`: argument defining the maximum sequence length for both input and output tokens. It is default to be `1024`.
 - `--max-prompt-len MAX_PROMPT_LEN`: argument defining the maximum number of tokens that the input prompt can contain. It is default to be `512`.
-- `--low-bit` LOW_BIT: argument defining the low bit optimizations that will be applied to the model. Current available options are `"sym_int4"`, `"asym_int4"` and `"sym_int8"`, with `"sym_int4"` as the default.
+- `--low-bit LOW_BIT`: argument defining the low bit optimizations that will be applied to the model. Current available options are `"sym_int4"`, `"asym_int4"` and `"sym_int8"`, with `"sym_int4"` as the default.
 
 ### Sample Output
 #### [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)