Pytorch models transformers version update (#11860)

* yi sync

* delete 4.34 constraint

* delete 4.34 constraint

* delete 4.31 constraint

* delete 4.34 constraint

* delete 4.35 constraint

* added <=4.33.3 constraint

* added <=4.33.3 constraint

* switched to chinese prompt

python/llm/example/GPU/HuggingFace/LLM/yi/README.md

@@ -122,18 +122,18 @@ In the example, several arguments can be passed to satisfy your requirements:
 ```log
 Inference time: xxxx s
 -------------------- Prompt --------------------
-What is AI?
+AI是什么？
 -------------------- Output --------------------
-What is AI?
+AI是什么？
-Artificial Intelligence (AI) is the simulation of human intelligence in machines. AI is the science and engineering of making intelligent machines, especially intelligent computer programs.
+人工智能（Artificial Intelligence），英文缩写为AI。它是研究、开发用于模拟、延伸和扩展人的智能的理论、方法、技术及
 ```
 
 #### [01-ai/Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat)
 ```log
 Inference time: xxxx s
 -------------------- Prompt --------------------
-What is AI?
+AI是什么？
 -------------------- Output --------------------
-What is AI?
+AI是什么？
-Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning, and self-
+人工智能（Artificial Intelligence, AI）是计算机科学的一个分支，它研究如何让计算机模拟人类的智能行为。人工智能可以通过模仿人类的思维过程和
 ```

python/llm/example/GPU/HuggingFace/LLM/yi/generate.py

@@ -27,7 +27,7 @@ if __name__ == '__main__':
     parser.add_argument('--repo-id-or-model-path', type=str, default="01-ai/Yi-6B-Chat",
                         help='The huggingface repo id for the Yi model to be downloaded'
                              ', or the path to the huggingface checkpoint folder')
-    parser.add_argument('--prompt', type=str, default="What is AI?",
+    parser.add_argument('--prompt', type=str, default="AI是什么？",
                         help='Prompt to infer')
     parser.add_argument('--n-predict', type=int, default=32,
                         help='Max tokens to predict')

python/llm/example/GPU/PyTorch-Models/Model/codegeex2/README.md

@@ -16,7 +16,6 @@ conda create -n llm python=3.11
 conda activate llm
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
-pip install transformers==4.31.0
 ```
 
 #### 1.2 Installation on Windows
@@ -27,7 +26,6 @@ conda activate llm
 
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
-pip install transformers==4.31.0
 ```
 
 ### 2. Configures OneAPI environment variables for Linux

python/llm/example/GPU/PyTorch-Models/Model/codellama/README.md

@@ -14,8 +14,6 @@ conda create -n llm python=3.11
 conda activate llm
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
-
-pip install transformers==4.34.1 # CodeLlamaTokenizer is supported in higher version of transformers
 ```
 
 #### 1.2 Installation on Windows
@@ -26,8 +24,6 @@ conda activate llm
 
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
-
-pip install transformers==4.34.1 # CodeLlamaTokenizer is supported in higher version of transformers
 ```
 
 ### 2. Configures OneAPI environment variables for Linux

python/llm/example/GPU/PyTorch-Models/Model/deciLM-7b/README.md

@@ -14,8 +14,6 @@ conda create -n llm python=3.11
 conda activate llm
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
-
-pip install transformers==4.35.2 # required by DeciLM-7B
 ```
 
 #### 1.2 Installation on Windows

python/llm/example/GPU/PyTorch-Models/Model/mistral/README.md

@@ -4,7 +4,6 @@ In this directory, you will find examples on how you could use IPEX-LLM `optimiz
 ## Requirements
 To run these examples with IPEX-LLM on Intel GPUs, we have some recommended requirements for your machine, please refer to [here](../../../README.md#requirements) for more information.
 
-**Important: According to [Mistral Troubleshooting](https://huggingface.co/mistralai/Mistral-7B-v0.1#troubleshooting), please make sure you have installed `transformers==4.34.0` to run the example.**
 
 ## Example: Predict Tokens using `generate()` API
 In the example [generate.py](./generate.py), we show a basic use case for a Mistral model to predict the next N tokens using `generate()` API, with IPEX-LLM INT4 optimizations on Intel GPUs.
@@ -16,9 +15,6 @@ conda create -n llm python=3.11
 conda activate llm
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
-
-# Refer to https://huggingface.co/mistralai/Mistral-7B-v0.1#troubleshooting, please make sure you are using a stable version of Transformers, 4.34.0 or newer.
-pip install transformers==4.34.0
 ```
 
 #### 1.2 Installation on Windows
@@ -29,9 +25,6 @@ conda activate llm
 
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
-
-# Refer to https://huggingface.co/mistralai/Mistral-7B-v0.1#troubleshooting, please make sure you are using a stable version of Transformers, 4.34.0 or newer.
-pip install transformers==4.34.0
 ```
 
 ### 2. Configures OneAPI environment variables for Linux

python/llm/example/GPU/PyTorch-Models/Model/replit/README.md

@@ -15,7 +15,7 @@ conda activate llm
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
 
-pip install "transformers<4.35"
+pip install transformers<=4.33.3
 ```
 
 #### 1.2 Installation on Windows
@@ -26,6 +26,8 @@ conda activate llm
 
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
+
+pip install transformers<=4.33.3
 ```
 
 ### 2. Configures OneAPI environment variables for Linux

python/llm/example/GPU/PyTorch-Models/Model/solar/README.md

@@ -14,8 +14,6 @@ conda create -n llm python=3.11
 conda activate llm
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
-
-pip install transformers==4.35.2 # required by SOLAR
 ```
 
 #### 1.2 Installation on Windows
@@ -26,8 +24,6 @@ conda activate llm
 
 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default
 pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
-
-pip install transformers==4.35.2 # required by SOLAR
 ```
 
 ### 2. Configures OneAPI environment variables for Linux

python/llm/example/GPU/PyTorch-Models/Model/yi/README.md

@@ -1,5 +1,5 @@
 # Yi
-In this directory, you will find examples on how you could use IPEX-LLM `optimize_model` API on Yi models on [Intel GPUs](../../../README.md). For illustration purposes, we utilize the [01-ai/Yi-6B](https://huggingface.co/01-ai/Yi-6B) as a reference Yi model.
+In this directory, you will find examples on how you could use IPEX-LLM `optimize_model` API on Yi models on [Intel GPUs](../../../README.md). For illustration purposes, we utilize the [01-ai/Yi-6B](https://huggingface.co/01-ai/Yi-6B) and [01-ai/Yi-6B-Chat](https://huggingface.co/01-ai/Yi-1.5-6B-Chat) as reference Yi models.
 
 ## 0. Requirements
 To run these examples with IPEX-LLM on Intel GPUs, we have some recommended requirements for your machine, please refer to [here](../../../README.md#requirements) for more information.
@@ -112,7 +112,7 @@ python ./generate.py
 
 In the example, several arguments can be passed to satisfy your requirements:
 
-- `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the Yi model (e.g. `01-ai/Yi-6B`) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'01-ai/Yi-6B'`.
+- `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the Yi model (e.g. `01-ai/Yi-6B` and `01-ai/Yi-6B-Chat`) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'01-ai/Yi-6B-Chat'`.
 - `--prompt PROMPT`: argument defining the prompt to be infered (with integrated prompt format for chat). It is default to be `'AI是什么？'`.
 - `--n-predict N_PREDICT`: argument defining the max number of tokens to predict. It is default to be `32`.
 
@@ -127,3 +127,13 @@ AI是什么？
 AI是什么？
 人工智能（Artificial Intelligence），英文缩写为AI。它是研究、开发用于模拟、延伸和扩展人的智能的理论、方法、技术及
 ```
+
+#### [01-ai/Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat)
+```log
+Inference time: xxxx s
+-------------------- Prompt --------------------
+AI是什么？
+-------------------- Output --------------------
+AI是什么？
+人工智能（Artificial Intelligence, AI）是计算机科学的一个分支，它研究如何让计算机模拟人类的智能行为。人工智能可以通过模仿人类的思维过程和
+```

python/llm/example/GPU/PyTorch-Models/Model/yi/generate.py

@@ -26,7 +26,7 @@ YI_PROMPT_FORMAT = "{prompt}"
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser(description='Predict Tokens using `generate()` API for Yi model')
-    parser.add_argument('--repo-id-or-model-path', type=str, default="01-ai/Yi-6B",
+    parser.add_argument('--repo-id-or-model-path', type=str, default="01-ai/Yi-6B-Chat",
                         help='The huggingface repo id for the Yi model to be downloaded'
                              ', or the path to the huggingface checkpoint folder')
     parser.add_argument('--prompt', type=str, default="AI是什么？",