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--- |
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license: apache-2.0 |
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language: |
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- en |
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tags: |
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- llama |
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- openchat |
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--- |
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Since this is an OpenChat model, here's the OpenChat card. |
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# OpenChat: Less is More for Open-source Models |
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OpenChat is a series of open-source language models fine-tuned on a diverse and high-quality dataset of multi-round conversations. With only ~6K GPT-4 conversations filtered from the ~90K ShareGPT conversations, OpenChat is designed to achieve high performance with limited data. |
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**Generic models:** |
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- OpenChat: based on LLaMA-13B (2048 context length) |
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- **🚀 105.7%** of ChatGPT score on Vicuna GPT-4 evaluation |
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- **🔥 80.9%** Win-rate on AlpacaEval |
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- **🤗 Only used 6K data for finetuning!!!** |
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- OpenChat-8192: based on LLaMA-13B (extended to 8192 context length) |
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- **106.6%** of ChatGPT score on Vicuna GPT-4 evaluation |
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- **79.5%** of ChatGPT score on Vicuna GPT-4 evaluation |
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**Code models:** |
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- OpenCoderPlus: based on StarCoderPlus (native 8192 context length) |
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- **102.5%** of ChatGPT score on Vicuna GPT-4 evaluation |
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- **78.7%** Win-rate on AlpacaEval |
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*Note:* Please load the pretrained models using *bfloat16* |
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## Code and Inference Server |
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We provide the full source code, including an inference server compatible with the "ChatCompletions" API, in the [OpenChat](https://github.com/imoneoi/openchat) GitHub repository. |
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## Web UI |
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OpenChat also includes a web UI for a better user experience. See the GitHub repository for instructions. |
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## Conversation Template |
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The conversation template **involves concatenating tokens**. |
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Besides base model vocabulary, an end-of-turn token `<|end_of_turn|>` is added, with id `eot_token_id`. |
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```python |
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# OpenChat |
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[bos_token_id] + tokenize("Human: ") + tokenize(user_question) + [eot_token_id] + tokenize("Assistant: ") |
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# OpenCoder |
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tokenize("User:") + tokenize(user_question) + [eot_token_id] + tokenize("Assistant:") |
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``` |
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*Hint: In BPE, `tokenize(A) + tokenize(B)` does not always equals to `tokenize(A + B)`* |
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Following is the code for generating the conversation templates: |
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```python |
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@dataclass |
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class ModelConfig: |
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# Prompt |
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system: Optional[str] |
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role_prefix: dict |
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ai_role: str |
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eot_token: str |
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bos_token: Optional[str] = None |
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# Get template |
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def generate_conversation_template(self, tokenize_fn, tokenize_special_fn, message_list): |
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tokens = [] |
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masks = [] |
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# begin of sentence (bos) |
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if self.bos_token: |
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t = tokenize_special_fn(self.bos_token) |
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tokens.append(t) |
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masks.append(False) |
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# System |
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if self.system: |
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t = tokenize_fn(self.system) + [tokenize_special_fn(self.eot_token)] |
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tokens.extend(t) |
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masks.extend([False] * len(t)) |
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# Messages |
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for idx, message in enumerate(message_list): |
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# Prefix |
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t = tokenize_fn(self.role_prefix[message["from"]]) |
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tokens.extend(t) |
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masks.extend([False] * len(t)) |
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# Message |
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if "value" in message: |
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t = tokenize_fn(message["value"]) + [tokenize_special_fn(self.eot_token)] |
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tokens.extend(t) |
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masks.extend([message["from"] == self.ai_role] * len(t)) |
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else: |
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assert idx == len(message_list) - 1, "Empty message for completion must be on the last." |
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return tokens, masks |
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MODEL_CONFIG_MAP = { |
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# OpenChat / OpenChat-8192 |
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"openchat": ModelConfig( |
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# Prompt |
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system=None, |
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role_prefix={ |
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"human": "Human: ", |
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"gpt": "Assistant: " |
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}, |
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ai_role="gpt", |
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eot_token="<|end_of_turn|>", |
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bos_token="<s>", |
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), |
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# OpenCoder / OpenCoderPlus |
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"opencoder": ModelConfig( |
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# Prompt |
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system=None, |
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role_prefix={ |
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"human": "User:", |
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"gpt": "Assistant:" |
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}, |
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ai_role="gpt", |
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eot_token="<|end_of_turn|>", |
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bos_token=None, |
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) |
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} |
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``` |
