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:gem: [Feature] New model enabled: gemma-7b
Browse files- README.md +1 -1
- apis/chat_api.py +7 -0
- messagers/message_composer.py +48 -2
- networks/message_streamer.py +3 -0
README.md
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@@ -15,7 +15,7 @@ Project link: https://github.com/Hansimov/hf-llm-api
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## Features
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- Available Models (2024/01/22): [#5](https://github.com/Hansimov/hf-llm-api/issues/5)
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- `mistral-7b`, `mixtral-8x7b`, `nous-mixtral-8x7b`
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- Adaptive prompt templates for different models
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- Support OpenAI API format
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- Enable api endpoint via official `openai-python` package
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## Features
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- Available Models (2024/01/22): [#5](https://github.com/Hansimov/hf-llm-api/issues/5)
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+
- `mistral-7b`, `mixtral-8x7b`, `nous-mixtral-8x7b`, `gemma-7b`
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- Adaptive prompt templates for different models
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- Support OpenAI API format
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- Enable api endpoint via official `openai-python` package
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apis/chat_api.py
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@@ -54,6 +54,13 @@ class ChatAPIApp:
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"created": 1700000000,
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"owned_by": "NousResearch",
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},
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],
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}
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return self.available_models
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"created": 1700000000,
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"owned_by": "NousResearch",
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},
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{
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"id": "gemma-7b",
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"description": "[google/gemma-7b-it]: https://huggingface.co/google/gemma-7b-it",
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"object": "model",
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"created": 1700000000,
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"owned_by": "Google",
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},
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],
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}
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return self.available_models
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messagers/message_composer.py
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@@ -10,6 +10,7 @@ class MessageComposer:
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"mistral-7b",
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"openchat-3.5",
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"nous-mixtral-8x7b",
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]
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def __init__(self, model: str = None):
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self.model = "mixtral-8x7b"
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self.system_roles = ["system"]
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self.inst_roles = ["user", "system", "inst"]
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self.answer_roles = ["assistant", "bot", "answer"]
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self.default_role = "user"
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def concat_messages_by_role(self, messages):
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# Hello, who are you?<|im_end|>
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# <|im_start|>assistant
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self.messages = messages
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self.merged_str = ""
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)
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self.merged_str_list.append(f"GPT4 Correct Assistant:\n")
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self.merged_str = "\n".join(self.merged_str_list)
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else:
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self.merged_str = "\n".join(
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[
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self.append_last_instruction_to_messages(
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inst_matches_list, pair_matches_list
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)
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else:
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self.messages = [
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{
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if __name__ == "__main__":
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model = "mixtral-8x7b"
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# model = "nous-mixtral-8x7b"
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composer = MessageComposer(model)
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messages = [
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{
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"mistral-7b",
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"openchat-3.5",
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"nous-mixtral-8x7b",
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"gemma-7b",
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]
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def __init__(self, model: str = None):
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self.model = "mixtral-8x7b"
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self.system_roles = ["system"]
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self.inst_roles = ["user", "system", "inst"]
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self.answer_roles = ["assistant", "bot", "answer", "model"]
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self.default_role = "user"
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def concat_messages_by_role(self, messages):
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# Hello, who are you?<|im_end|>
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# <|im_start|>assistant
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# Google Gemma-it
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# <start_of_turn>user
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# How does the brain work?<end_of_turn>
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# <start_of_turn>model
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self.messages = messages
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self.merged_str = ""
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)
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self.merged_str_list.append(f"GPT4 Correct Assistant:\n")
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self.merged_str = "\n".join(self.merged_str_list)
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# https://huggingface.co/google/gemma-7b-it#chat-template
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elif self.model in ["gemma-7b"]:
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self.messages = self.concat_messages_by_role(messages)
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self.merged_str_list = []
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self.end_of_turn = "<end_of_turn>"
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self.start_of_turn = "<start_of_turn>"
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for message in self.messages:
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role = message["role"]
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content = message["content"]
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if role in self.inst_roles:
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self.merged_str_list.append(
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f"{self.start_of_turn}user\n{content}{self.end_of_turn}"
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)
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elif role in self.answer_roles:
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self.merged_str_list.append(
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f"{self.start_of_turn}model\n{content}{self.end_of_turn}"
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)
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else:
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self.merged_str_list.append(
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f"{self.start_of_turn}user\n{content}{self.end_of_turn}"
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)
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self.merged_str_list.append(f"{self.start_of_turn}model\n")
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self.merged_str = "\n".join(self.merged_str_list)
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else:
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self.merged_str = "\n".join(
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[
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self.append_last_instruction_to_messages(
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inst_matches_list, pair_matches_list
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)
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# https://huggingface.co/google/gemma-7b-it#chat-template
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elif self.model in ["gemma-7b"]:
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pair_pattern = r"<start_of_turn>user[\s\n]*(?P<inst>[\s\S]*?)<end_of_turn>[\s\n]*<start_of_turn>model(?P<answer>[\s\S]*?)<end_of_turn>"
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pair_matches = re.finditer(
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pair_pattern, self.merged_str, flags=re.MULTILINE | re.IGNORECASE
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)
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pair_matches_list = list(pair_matches)
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self.messages = self.convert_pair_matches_to_messages(pair_matches_list)
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inst_pattern = r"<start_of_turn>user\n(?P<inst>[\s\S]*?)<end_of_turn>"
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inst_matches = re.finditer(
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inst_pattern, self.merged_str, flags=re.MULTILINE | re.IGNORECASE
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)
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inst_matches_list = list(inst_matches)
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self.append_last_instruction_to_messages(
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inst_matches_list, pair_matches_list
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)
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else:
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self.messages = [
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{
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if __name__ == "__main__":
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# model = "mixtral-8x7b"
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# model = "nous-mixtral-8x7b"
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model = "gemma-7b"
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composer = MessageComposer(model)
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messages = [
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{
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networks/message_streamer.py
CHANGED
@@ -12,6 +12,7 @@ class MessageStreamer:
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"mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1", # 72.62, fast [Recommended]
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"mistral-7b": "mistralai/Mistral-7B-Instruct-v0.2", # 65.71, fast
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"nous-mixtral-8x7b": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
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# "openchat-3.5": "openchat/openchat-3.5-1210", # 68.89, fast
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# "zephyr-7b-beta": "HuggingFaceH4/zephyr-7b-beta", # ❌ Too Slow
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# "llama-70b": "meta-llama/Llama-2-70b-chat-hf", # ❌ Require Pro User
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"mistral-7b": "</s>",
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"nous-mixtral-8x7b": "<|im_end|>",
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"openchat-3.5": "<|end_of_turn|>",
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}
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TOKEN_LIMIT_MAP = {
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"mixtral-8x7b": 32768,
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"mistral-7b": 32768,
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"nous-mixtral-8x7b": 32768,
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"openchat-3.5": 8192,
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}
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TOKEN_RESERVED = 100
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"mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1", # 72.62, fast [Recommended]
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"mistral-7b": "mistralai/Mistral-7B-Instruct-v0.2", # 65.71, fast
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"nous-mixtral-8x7b": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
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"gemma-7b": "google/gemma-7b-it",
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# "openchat-3.5": "openchat/openchat-3.5-1210", # 68.89, fast
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# "zephyr-7b-beta": "HuggingFaceH4/zephyr-7b-beta", # ❌ Too Slow
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# "llama-70b": "meta-llama/Llama-2-70b-chat-hf", # ❌ Require Pro User
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"mistral-7b": "</s>",
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"nous-mixtral-8x7b": "<|im_end|>",
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"openchat-3.5": "<|end_of_turn|>",
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"gemma-7b": "<eos>",
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}
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TOKEN_LIMIT_MAP = {
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"mixtral-8x7b": 32768,
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"mistral-7b": 32768,
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"nous-mixtral-8x7b": 32768,
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"openchat-3.5": 8192,
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"gemma-7b": 8192,
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}
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TOKEN_RESERVED = 100
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