remove invalid LLM pretraining examples (#5583)

Author: 1pikachu

examples/gpu/llm/README.md

@@ -5,7 +5,7 @@ Here you can find examples for large language models (LLM) text generation. Thes
 > [!NOTE]  
 > New Llama models like Llama3.2-1B, Llama3.2-3B and Llama3.3-7B are also supported from release v2.7.10+xpu.
 
-- Include both inference/finetuning(lora)/bitsandbytes(qlora-finetuning)/training.
+- Include both inference/finetuning(lora)/bitsandbytes(qlora-finetuning).
 - Include both single instance and distributed (DeepSpeed) use cases for FP16 optimization.
 - Support Llama, GPT-J, Qwen, OPT, Bloom model families and some other models such as Baichuan2-13B and Phi3-mini. 
 - Cover model generation inference with low precision cases for different models with best performance and accuracy (fp16 AMP and weight only quantization)
@@ -32,7 +32,7 @@ docker run -it --rm --privileged -v /dev/dri/by-path:/dev/dri/by-path ipex-llm:x
 cd llm
 
 # Activate environment variables
-source ./tools/env_activate.sh  [inference|fine-tuning|bitsandbytes|training]
+source ./tools/env_activate.sh  [inference|fine-tuning|bitsandbytes]
 # on Windows, use env_activate.bat instead
 call .\tools\env_activate.bat [inference|fine-tuning|bitsandbytes]
 ```
@@ -59,7 +59,7 @@ cd examples/gpu/llm
 python ./tools/env_setup.py --setup --deploy
 conda deactivate
 conda activate llm
-source ./tools/env_activate.sh  [inference|fine-tuning|bitsandbytes|training]
+source ./tools/env_activate.sh  [inference|fine-tuning|bitsandbytes]
 # on Windows, use env_activate.bat instead
 call .\tools\env_activate.bat [inference|fine-tuning|bitsandbytes]
 ```
@@ -84,7 +84,7 @@ docker run -it --rm --privileged -v /dev/dri/by-path:/dev/dri/by-path ipex-llm:x
 cd llm
 
 # Activate environment variables
-source ./tools/env_activate.sh [inference|fine-tuning|bitsandbytes|training]
+source ./tools/env_activate.sh [inference|fine-tuning|bitsandbytes]
 # on Windows, use env_activate.bat instead
 call .\tools\env_activate.bat [inference|fine-tuning|bitsandbytes]
 ```
@@ -114,7 +114,7 @@ python ./tools/env_setup.py --setup --install-pytorch compile --aot <AOT> --onea
 
 conda deactivate
 conda activate llm
-source ./tools/env_activate.sh [inference|fine-tuning|bitsandbytes|training]
+source ./tools/env_activate.sh [inference|fine-tuning|bitsandbytes]
 # on Windows, use env_activate.bat instead
 call .\tools\env_activate.bat [inference|fine-tuning|bitsandbytes]
 ```
@@ -135,4 +135,3 @@ For fine-tuning example scripts, visit the [fine-tuning](./fine-tuning/) directo
 
 For fine-tuning with quantized model, visit the [bitsandbytes](./bitsandbytes/) directory.
 
-For fine-tuning with quantized model, visit the [training](./training/) directory.

examples/gpu/llm/tools/env_activate.bat

@@ -14,7 +14,7 @@ if "%~1"=="" (
 set MODE=%1
 
 :: Validate MODE
-if not "%MODE%"=="inference" if not "%MODE%"=="fine-tuning" if not "%MODE%"=="bitsandbytes" if not "%MODE%"=="training" (
+if not "%MODE%"=="inference" if not "%MODE%"=="fine-tuning" if not "%MODE%"=="bitsandbytes" (
     echo !MSG_USAGE!
     exit /b 2
 )

examples/gpu/llm/tools/env_activate.py

@@ -23,7 +23,7 @@
         'directory',
         help = 'Directory of examples to run.',
         type = str,
-        choices = ['inference', 'fine-tuning', 'bitsandbytes', 'training'],
+        choices = ['inference', 'fine-tuning', 'bitsandbytes'],
     )
 
     # Parse arguments

examples/gpu/llm/tools/env_activate.sh

@@ -1,12 +1,12 @@
 #!/bin/bash
 
-MSG_USAGE="Usage: source $0 [inference|fine-tuning|bitsandbytes|training]"
+MSG_USAGE="Usage: source $0 [inference|fine-tuning|bitsandbytes]"
 if [ $# -eq 0 ]; then
     echo ${MSG_USAGE}
     return 1
 fi
 MODE=$1
-if [ ${MODE} != "inference" ] && [ ${MODE} != "fine-tuning" ] && [ ${MODE} != "bitsandbytes" ] && [ ${MODE} != "training" ]; then
+if [ ${MODE} != "inference" ] && [ ${MODE} != "fine-tuning" ] && [ ${MODE} != "bitsandbytes" ]; then
     echo ${MSG_USAGE}
     return 2
 fi