Openchat

🚀 OpenChat: Less is More for Open-source Models

OpenChat is a series of open - source language models. These models are fine - tuned on a diverse and high - quality multi - round conversation dataset. By filtering only about 6K GPT - 4 conversations from approximately 90K ShareGPT conversations, OpenChat aims to achieve high performance with limited data.

✨ Features

Generic models

• OpenChat: Based on LLaMA - 13B (2048 context length)
  • Achieves 🚀 105.7% of ChatGPT score on Vicuna GPT - 4 evaluation.
  • Has a 🔥 80.9% win - rate on AlpacaEval.
  • 🤗 Only used 6K data for finetuning!!!
• OpenChat - 8192: Based on LLaMA - 13B (extended to 8192 context length)
  • Gets 106.6% of ChatGPT score on Vicuna GPT - 4 evaluation.
  • Has a 79.5% win - rate on AlpacaEval.

Code models

• OpenCoderPlus: Based on StarCoderPlus (native 8192 context length)
  • Achieves 102.5% of ChatGPT score on Vicuna GPT - 4 evaluation.
  • Has a 78.7% win - rate on AlpacaEval.

⚠️ Important Note

Please load the pretrained models using bfloat16.

📦 Installation

No installation steps are provided in the original document, so this section is skipped.

💻 Usage Examples

Basic Usage

The conversation template involves concatenating tokens. Besides base model vocabulary, an end - of - turn token <|end_of_turn|> is added, with id eot_token_id.

# OpenChat
[bos_token_id] + tokenize("Human: ") + tokenize(user_question) + [eot_token_id] + tokenize("Assistant: ")
# OpenCoder
tokenize("User:") + tokenize(user_question) + [eot_token_id] + tokenize("Assistant:")

💡 Usage Tip

In BPE, tokenize(A) + tokenize(B) does not always equal to tokenize(A + B).

Advanced Usage

Following is the code for generating the conversation templates:

@dataclass
class ModelConfig:
    # Prompt
    system: Optional[str]

    role_prefix: dict
    ai_role: str
    eot_token: str
    bos_token: Optional[str] = None

    # Get template
    def generate_conversation_template(self, tokenize_fn, tokenize_special_fn, message_list):
        tokens = []
        masks = []

        # begin of sentence (bos)
        if self.bos_token:
            t = tokenize_special_fn(self.bos_token)
            tokens.append(t)
            masks.append(False)

        # System
        if self.system:
            t = tokenize_fn(self.system) + [tokenize_special_fn(self.eot_token)]
            tokens.extend(t)
            masks.extend([False] * len(t))

        # Messages
        for idx, message in enumerate(message_list):
            # Prefix
            t = tokenize_fn(self.role_prefix[message["from"]])
            tokens.extend(t)
            masks.extend([False] * len(t))

            # Message
            if "value" in message:
                t = tokenize_fn(message["value"]) + [tokenize_special_fn(self.eot_token)]
                tokens.extend(t)
                masks.extend([message["from"] == self.ai_role] * len(t))
            else:
                assert idx == len(message_list) - 1, "Empty message for completion must be on the last."

        return tokens, masks


MODEL_CONFIG_MAP = {
    # OpenChat / OpenChat-8192
    "openchat": ModelConfig(
        # Prompt
        system=None,

        role_prefix={
            "human": "Human: ",
            "gpt": "Assistant: "
        },
        ai_role="gpt",
        eot_token="<|end_of_turn|>",
        bos_token="<s>",
    ),

    # OpenCoder / OpenCoderPlus
    "opencoder": ModelConfig(
        # Prompt
        system=None,

        role_prefix={
            "human": "User:",
            "gpt": "Assistant:"
        },
        ai_role="gpt",
        eot_token="<|end_of_turn|>",
        bos_token=None,
    )
}

📚 Documentation

Code and Inference Server

We provide the full source code, including an inference server compatible with the "ChatCompletions" API, in the OpenChat GitHub repository.

Web UI

OpenChat also includes a web UI for a better user experience. See the GitHub repository for instructions.

📄 License

Our weight license is subject to their corresponding base model. For example, OpenChat and OpenChat - 8192 are the same as the model License of LLaMA for non - commercial use only, while OpenCoderPlus is under the License of StarCoder. Furthermore, we should follow the [Privacy Practices](https://chrome.google.com/webstore/detail/sharegpt - share - your - chatg/daiacboceoaocpibfodeljbdfacokfjb) of ShareGPT. The code released on GitHub is under Apache License 2.0.

📚 Citation

@software{openllms23,
  title = {{OpenLLMs: Less is More for Open-source Models}},
  author = {Wang, Guan and Cheng, Sijie and Yu, Qiying and Liu, Changling},
  doi = {10.5281/zenodo.8105775},
  url = {https://github.com/imoneoi/openchat},
  version = {pre-release},
  year = {2023},
  month = {7},
}