[LLM] Small fixes for finetune related examples and UTs (#9870)

.github/workflows/llm_unit_tests.yml

@@ -324,7 +324,8 @@ jobs:
       - name: Run LLM example tests
         shell: bash
         run: |
-          python -m pip install transformers==4.34.0 peft==0.5.0 accelerate==0.23.0
+          python -m pip uninstall datasets -y
+          python -m pip install transformers==4.34.0 datasets peft==0.5.0 accelerate==0.23.0
           python -m pip install bitsandbytes scipy
           # Specific oneapi position on arc ut test machines
           if [[ '${{ matrix.pytorch-version }}' == '2.1' ]]; then

python/llm/example/GPU/QLoRA-FineTuning/README.md

@@ -16,7 +16,7 @@ conda create -n llm python=3.9
 conda activate llm
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade bigdl-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu
-pip install datasets transformers==4.34.0
+pip install transformers==4.34.0 datasets
 pip install peft==0.5.0
 pip install accelerate==0.23.0
 pip install bitsandbytes scipy

python/llm/example/GPU/QLoRA-FineTuning/alpaca-qlora/README.md

@@ -12,7 +12,7 @@ conda create -n llm python=3.9
 conda activate llm
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade bigdl-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu
-pip install datasets transformers==4.34.0
+pip install transformers==4.34.0 datasets
 pip install fire peft==0.5.0
 pip install oneccl_bind_pt==2.1.100 -f https://developer.intel.com/ipex-whl-stable-xpu # necessary to run distributed finetuning
 pip install accelerate==0.23.0