LlaMA 3 系列博客

基于 LlaMA 3 + LangGraph 在windows本地部署大模型 （一）

基于 LlaMA 3 + LangGraph 在windows本地部署大模型 （二）

基于 LlaMA 3 + LangGraph 在windows本地部署大模型 （三）

基于 LlaMA 3 + LangGraph 在windows本地部署大模型 （四）

基于 LlaMA 3 + LangGraph 在windows本地部署大模型 （五）

基于 LlaMA 3 + LangGraph 在windows本地部署大模型 （六）

基于 LlaMA 3 + LangGraph 在windows本地部署大模型 （七）

基于 LlaMA 3 + LangGraph 在windows本地部署大模型 （八）

基于 LlaMA 3 + LangGraph 在windows本地部署大模型 （九）

基于 LlaMA 3 + LangGraph 在windows本地部署大模型 （十）

构建安全的GenAI/LLMs核心技术解密之大模型对抗攻击（一）

构建安全的GenAI/LLMs核心技术解密之大模型对抗攻击（二）

构建安全的GenAI/LLMs核心技术解密之大模型对抗攻击（三）

构建安全的GenAI/LLMs核心技术解密之大模型对抗攻击（四）

构建安全的GenAI/LLMs核心技术解密之大模型对抗攻击（五）

你好 GPT-4o！

大模型标记器之Tokenizer可视化（GPT-4o）

大模型标记器 Tokenizer之Byte Pair Encoding (BPE) 算法详解与示例

大模型标记器 Tokenizer之Byte Pair Encoding (BPE)源码分析

大模型之自注意力机制Self-Attention（一）

大模型之自注意力机制Self-Attention（二）

大模型之自注意力机制Self-Attention（三）

基于 LlaMA 3 + LangGraph 在windows本地部署大模型 （十一）

Llama 3 模型家族构建安全可信赖企业级AI应用之 Code Llama （一）

Llama 3 模型家族构建安全可信赖企业级AI应用之 Code Llama （二）

Llama 3 模型家族构建安全可信赖企业级AI应用之 Code Llama （三）

Llama 3 模型家族构建安全可信赖企业级AI应用之 Code Llama （四）

Llama 3 模型家族构建安全可信赖企业级AI应用之 Code Llama （五）

Llama 3 模型家族构建安全可信赖企业级AI应用之使用 Llama Guard 保护大模型对话（一）

Llama 3 模型家族构建安全可信赖企业级AI应用之使用 Llama Guard 保护大模型对话（二）

Llama 3 模型家族构建安全可信赖企业级AI应用之使用 Llama Guard 保护大模型对话（三）

大模型之深入理解Transformer位置编码（Positional Embedding）

大模型之深入理解Transformer Layer Normalization（一）

大模型之深入理解Transformer Layer Normalization（二）

大模型之深入理解Transformer Layer Normalization（三）

大模型之一步一步使用PyTorch编写Meta的Llama 3代码（一）初学者的起点

大模型之一步一步使用PyTorch编写Meta的Llama 3代码（二）矩阵操作的演练

大模型之一步一步使用PyTorch编写Meta的Llama 3代码（三）初始化一个嵌入层

大模型之一步一步使用PyTorch编写Meta的Llama 3代码（四）预先计算 RoPE 频率

大模型之一步一步使用PyTorch编写Meta的Llama 3代码（五）预先计算因果掩码

大模型之一步一步使用PyTorch编写Meta的Llama 3代码（六）首次归一化：均方根归一化（RMSNorm）

大模型之一步一步使用PyTorch编写Meta的Llama 3代码（七） 初始化多查询注意力

大模型之一步一步使用PyTorch编写Meta的Llama 3代码（八）旋转位置嵌入

大模型之一步一步使用PyTorch编写Meta的Llama 3代码（九） 计算自注意力

大模型之一步一步使用PyTorch编写Meta的Llama 3代码（十） 残差连接及SwiGLU FFN

大模型之一步一步使用PyTorch编写Meta的Llama 3代码（十一）输出概率分布 及损失函数计算

大模型之使用PyTorch编写Meta的Llama 3实际功能代码（一）加载简化分词器及设置参数

大模型之使用PyTorch编写Meta的Llama 3实际功能代码（二）RoPE 及注意力机制

大模型之使用PyTorch编写Meta的Llama 3实际功能代码（三） FeedForward 及 Residual Layers

大模型之使用PyTorch编写Meta的Llama 3实际功能代码（四） 构建 Llama3 类模型本身

大模型之使用PyTorch编写Meta的Llama 3实际功能代码（五）训练并测试你自己的 minLlama3

大模型之使用PyTorch编写Meta的Llama 3实际功能代码（六）加载已经训练好的miniLlama3模型

Llama 3 模型家族构建安全可信赖企业级AI应用之使用 Llama Guard 保护大模型对话 （四）

Llama 3 模型家族构建安全可信赖企业级AI应用之使用 Llama Guard 保护大模型对话 （五）

Llama 3 模型家族构建安全可信赖企业级AI应用之使用 Llama Guard 保护大模型对话 （六）

Llama 3 模型家族构建安全可信赖企业级AI应用之使用 Llama Guard 保护大模型对话 （七）

Llama 3 模型家族构建安全可信赖企业级AI应用之使用 Llama Guard 保护大模型对话 （八）

Llama 3 模型家族构建安全可信赖企业级AI应用之 CyberSecEval 2：量化 LLM 安全和能力的基准（一）

Llama 3 模型家族构建安全可信赖企业级AI应用之 CyberSecEval 2：量化 LLM 安全和能力的基准（二）

Llama 3 模型家族构建安全可信赖企业级AI应用之 CyberSecEval 2：量化 LLM 安全和能力的基准（三）

Llama 3 模型家族构建安全可信赖企业级AI应用之 CyberSecEval 2：量化 LLM 安全和能力的基准（四）

Llama 3 模型家族构建安全可信赖企业级AI应用之code shield（一）Code Shield简介

Llama 3 模型家族构建安全可信赖企业级AI应用之code shield（二）防止 LLM 生成不安全代码

Llama 3 模型家族构建安全可信赖企业级AI应用之code shield（三）Code Shield代码示例

Llama模型家族之使用 Supervised Fine-Tuning（SFT）微调预训练Llama 3 语言模型（一） LLaMA-Factory简介

微调大模型可以像这样轻松…

LLaMA-Factory 项目特色

• 多种模型：LLaMA、LLaVA、Mistral、Mixtral-MoE、Qwen、Yi、Gemma、Baichuan、ChatGLM、Phi 等等。
• 集成方法：（增量）预训练、（多模态）指令监督微调、奖励模型训练、PPO 训练、DPO 训练、KTO 训练和 ORPO 训练。
• 多种精度：32 比特全参数微调、16 比特冻结微调、16 比特 LoRA 微调和基于 AQLM/AWQ/GPTQ/LLM.int8 的 2/4/8 比特 QLoRA 微调。
• 先进算法：GaLore、BAdam、DoRA、LongLoRA、LLaMA Pro、Mixture-of-Depths、LoRA+、LoftQ 和 Agent 微调。
• 实用技巧：FlashAttention-2、Unsloth、RoPE scaling、NEFTune 和 rsLoRA。
• 实验监控：LlamaBoard、TensorBoard、Wandb、MLflow 等等。
• 极速推理：基于 vLLM 的 OpenAI 风格 API、浏览器界面和命令行接口。

性能指标

与 ChatGLM 官方的 P-Tuning 微调相比，LLaMA Factory 的 LoRA 微调提供了 3.7 倍的加速比，同时在广告文案生成任务上取得了更高的 Rouge 分数。结合 4 比特量化技术，LLaMA Factory 的 QLoRA 微调进一步降低了 GPU 显存消耗。

• Training Speed: 训练阶段每秒处理的样本数量。（批处理大小=4，截断长度=1024）
• Rouge Score: 广告文案生成任务验证集上的 Rouge-2 分数。（批处理大小=4，截断长度=1024）
• GPU Memory: 4 比特量化训练的 GPU 显存峰值。（批处理大小=1，截断长度=1024）
• 在 ChatGLM 的 P-Tuning 中采用 pre_seq_len=128，在 LLaMA Factory 的 LoRA 微调中采用 lora_rank=32。

更新日志

[24/05/20] 官网支持了 PaliGemma 系列模型的微调。注意 PaliGemma 是预训练模型，你需要使用 gemma 模板进行微调使其获得对话能力。

[24/05/18] 官网支持了 KTO 偏好对齐算法。详细用法请参照 examples。

https://arxiv.org/pdf/2402.01306
[24/05/14] 官网支持了昇腾 NPU 设备的训练和推理。

模型

默认模块应作为 --lora_target 参数的默认值，可使用 --lora_target all 参数指定全部模块以取得更好的效果。

对于所有“基座”（Base）模型，–template 参数可以是 default, alpaca, vicuna 等任意值。但“对话”（Instruct/Chat）模型请务必使用对应的模板。

项目所支持模型的完整列表：

from collections import OrderedDict, defaultdict
from enum import Enum
from typing import Dict, OptionalCHOICES = ["A", "B", "C", "D"]DATA_CONFIG = "dataset_info.json"DEFAULT_MODULE = defaultdict(str)DEFAULT_TEMPLATE = defaultdict(str)FILEEXT2TYPE = {"arrow": "arrow","csv": "csv","json": "json","jsonl": "json","parquet": "parquet","txt": "text",
}IGNORE_INDEX = -100IMAGE_TOKEN = "<image>"LAYERNORM_NAMES = {"norm", "ln"}METHODS = ["full", "freeze", "lora"]MOD_SUPPORTED_MODELS = ["bloom", "falcon", "gemma", "llama", "mistral", "mixtral", "phi", "starcoder2"]PEFT_METHODS = ["lora"]RUNNING_LOG = "running_log.txt"SUBJECTS = ["Average", "STEM", "Social Sciences", "Humanities", "Other"]SUPPORTED_MODELS = OrderedDict()TRAINER_CONFIG = "trainer_config.yaml"TRAINER_LOG = "trainer_log.jsonl"TRAINING_STAGES = {"Supervised Fine-Tuning": "sft","Reward Modeling": "rm","PPO": "ppo","DPO": "dpo","KTO": "kto","ORPO": "orpo","Pre-Training": "pt",
}STAGES_USE_PAIR_DATA = ["rm", "dpo", "orpo"]SUPPORTED_CLASS_FOR_S2ATTN = ["llama"]V_HEAD_WEIGHTS_NAME = "value_head.bin"V_HEAD_SAFE_WEIGHTS_NAME = "value_head.safetensors"VISION_MODELS = set()class DownloadSource(str, Enum):DEFAULT = "hf"MODELSCOPE = "ms"def register_model_group(models: Dict[str, Dict[DownloadSource, str]],module: Optional[str] = None,template: Optional[str] = None,vision: bool = False,
) -> None:prefix = Nonefor name, path in models.items():if prefix is None:prefix = name.split("-")[0]else:assert prefix == name.split("-")[0], "prefix should be identical."SUPPORTED_MODELS[name] = pathif module is not None:DEFAULT_MODULE[prefix] = moduleif template is not None:DEFAULT_TEMPLATE[prefix] = templateif vision:VISION_MODELS.add(prefix)register_model_group(models={"Baichuan-7B-Base": {DownloadSource.DEFAULT: "baichuan-inc/Baichuan-7B",DownloadSource.MODELSCOPE: "baichuan-inc/baichuan-7B",},"Baichuan-13B-Base": {DownloadSource.DEFAULT: "baichuan-inc/Baichuan-13B-Base",DownloadSource.MODELSCOPE: "baichuan-inc/Baichuan-13B-Base",},"Baichuan-13B-Chat": {DownloadSource.DEFAULT: "baichuan-inc/Baichuan-13B-Chat",DownloadSource.MODELSCOPE: "baichuan-inc/Baichuan-13B-Chat",},},module="W_pack",template="baichuan",
)register_model_group(models={"Baichuan2-7B-Base": {DownloadSource.DEFAULT: "baichuan-inc/Baichuan2-7B-Base",DownloadSource.MODELSCOPE: "baichuan-inc/Baichuan2-7B-Base",},"Baichuan2-13B-Base": {DownloadSource.DEFAULT: "baichuan-inc/Baichuan2-13B-Base",DownloadSource.MODELSCOPE: "baichuan-inc/Baichuan2-13B-Base",},"Baichuan2-7B-Chat": {DownloadSource.DEFAULT: "baichuan-inc/Baichuan2-7B-Chat",DownloadSource.MODELSCOPE: "baichuan-inc/Baichuan2-7B-Chat",},"Baichuan2-13B-Chat": {DownloadSource.DEFAULT: "baichuan-inc/Baichuan2-13B-Chat",DownloadSource.MODELSCOPE: "baichuan-inc/Baichuan2-13B-Chat",},},module="W_pack",template="baichuan2",
)register_model_group(models={"BLOOM-560M": {DownloadSource.DEFAULT: "bigscience/bloom-560m",DownloadSource.MODELSCOPE: "AI-ModelScope/bloom-560m",},"BLOOM-3B": {DownloadSource.DEFAULT: "bigscience/bloom-3b",DownloadSource.MODELSCOPE: "AI-ModelScope/bloom-3b",},"BLOOM-7B1": {DownloadSource.DEFAULT: "bigscience/bloom-7b1",DownloadSource.MODELSCOPE: "AI-ModelScope/bloom-7b1",},},module="query_key_value",
)register_model_group(models={"BLOOMZ-560M": {DownloadSource.DEFAULT: "bigscience/bloomz-560m",DownloadSource.MODELSCOPE: "AI-ModelScope/bloomz-560m",},"BLOOMZ-3B": {DownloadSource.DEFAULT: "bigscience/bloomz-3b",DownloadSource.MODELSCOPE: "AI-ModelScope/bloomz-3b",},"BLOOMZ-7B1-mt": {DownloadSource.DEFAULT: "bigscience/bloomz-7b1-mt",DownloadSource.MODELSCOPE: "AI-ModelScope/bloomz-7b1-mt",},},module="query_key_value",
)register_model_group(models={"BlueLM-7B-Base": {DownloadSource.DEFAULT: "vivo-ai/BlueLM-7B-Base",DownloadSource.MODELSCOPE: "vivo-ai/BlueLM-7B-Base",},"BlueLM-7B-Chat": {DownloadSource.DEFAULT: "vivo-ai/BlueLM-7B-Chat",DownloadSource.MODELSCOPE: "vivo-ai/BlueLM-7B-Chat",},},template="bluelm",
)register_model_group(models={"Breeze-7B": {DownloadSource.DEFAULT: "MediaTek-Research/Breeze-7B-Base-v1_0",},"Breeze-7B-Chat": {DownloadSource.DEFAULT: "MediaTek-Research/Breeze-7B-Instruct-v1_0",},},template="breeze",
)register_model_group(models={"ChatGLM2-6B-Chat": {DownloadSource.DEFAULT: "THUDM/chatglm2-6b",DownloadSource.MODELSCOPE: "ZhipuAI/chatglm2-6b",}},module="query_key_value",template="chatglm2",
)register_model_group(models={"ChatGLM3-6B-Base": {DownloadSource.DEFAULT: "THUDM/chatglm3-6b-base",DownloadSource.MODELSCOPE: "ZhipuAI/chatglm3-6b-base",},"ChatGLM3-6B-Chat": {DownloadSource.DEFAULT: "THUDM/chatglm3-6b",DownloadSource.MODELSCOPE: "ZhipuAI/chatglm3-6b",},},module="query_key_value",template="chatglm3",
)register_model_group(models={"ChineseLLaMA2-1.3B": {DownloadSource.DEFAULT: "hfl/chinese-llama-2-1.3b",DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-llama-2-1.3b",},"ChineseLLaMA2-7B": {DownloadSource.DEFAULT: "hfl/chinese-llama-2-7b",DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-llama-2-7b",},"ChineseLLaMA2-13B": {DownloadSource.DEFAULT: "hfl/chinese-llama-2-13b",DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-llama-2-13b",},"ChineseLLaMA2-1.3B-Chat": {DownloadSource.DEFAULT: "hfl/chinese-alpaca-2-1.3b",DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-alpaca-2-1.3b",},"ChineseLLaMA2-7B-Chat": {DownloadSource.DEFAULT: "hfl/chinese-alpaca-2-7b",DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-alpaca-2-7b",},"ChineseLLaMA2-13B-Chat": {DownloadSource.DEFAULT: "hfl/chinese-alpaca-2-13b",DownloadSource.MODELSCOPE: "AI-ModelScope/chinese-alpaca-2-13b",},},template="llama2_zh",
)register_model_group(models={"CommandR-35B-Chat": {DownloadSource.DEFAULT: "CohereForAI/c4ai-command-r-v01",DownloadSource.MODELSCOPE: "AI-ModelScope/c4ai-command-r-v01",},"CommandR-Plus-104B-Chat": {DownloadSource.DEFAULT: "CohereForAI/c4ai-command-r-plus",DownloadSource.MODELSCOPE: "AI-ModelScope/c4ai-command-r-plus",},"CommandR-35B-4bit-Chat": {DownloadSource.DEFAULT: "CohereForAI/c4ai-command-r-v01-4bit",DownloadSource.MODELSCOPE: "mirror013/c4ai-command-r-v01-4bit",},"CommandR-Plus-104B-4bit-Chat": {DownloadSource.DEFAULT: "CohereForAI/c4ai-command-r-plus-4bit",},},template="cohere",
)register_model_group(models={"DBRX-132B-Base": {DownloadSource.DEFAULT: "databricks/dbrx-base",DownloadSource.MODELSCOPE: "AI-ModelScope/dbrx-base",},"DBRX-132B-Chat": {DownloadSource.DEFAULT: "databricks/dbrx-instruct",DownloadSource.MODELSCOPE: "AI-ModelScope/dbrx-instruct",},},module="Wqkv",template="dbrx",
)register_model_group(models={"DeepSeek-LLM-7B-Base": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-llm-7b-base",DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-llm-7b-base",},"DeepSeek-LLM-67B-Base": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-llm-67b-base",DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-llm-67b-base",},"DeepSeek-LLM-7B-Chat": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-llm-7b-chat",DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-llm-7b-chat",},"DeepSeek-LLM-67B-Chat": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-llm-67b-chat",DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-llm-67b-chat",},"DeepSeek-Math-7B-Base": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-math-7b-base",DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-math-7b-base",},"DeepSeek-Math-7B-Chat": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-math-7b-instruct",DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-math-7b-instruct",},"DeepSeek-MoE-16B-Base": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-moe-16b-base",DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-moe-16b-base",},"DeepSeek-MoE-16B-v2-Base": {DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2-Lite",},"DeepSeek-MoE-236B-Base": {DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2",DownloadSource.MODELSCOPE: "deepseek-ai/DeepSeek-V2",},"DeepSeek-MoE-16B-Chat": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-moe-16b-chat",DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-moe-16b-chat",},"DeepSeek-MoE-16B-v2-Chat": {DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2-Lite-Chat",},"DeepSeek-MoE-236B-Chat": {DownloadSource.DEFAULT: "deepseek-ai/DeepSeek-V2-Chat",DownloadSource.MODELSCOPE: "deepseek-ai/DeepSeek-V2-Chat",},},template="deepseek",
)register_model_group(models={"DeepSeekCoder-6.7B-Base": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-6.7b-base",DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-coder-6.7b-base",},"DeepSeekCoder-7B-Base": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-7b-base-v1.5",},"DeepSeekCoder-33B-Base": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-33b-base",DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-coder-33b-base",},"DeepSeekCoder-6.7B-Chat": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-6.7b-instruct",DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-coder-6.7b-instruct",},"DeepSeekCoder-7B-Chat": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-7b-instruct-v1.5",},"DeepSeekCoder-33B-Chat": {DownloadSource.DEFAULT: "deepseek-ai/deepseek-coder-33b-instruct",DownloadSource.MODELSCOPE: "deepseek-ai/deepseek-coder-33b-instruct",},},template="deepseekcoder",
)register_model_group(models={"Falcon-7B": {DownloadSource.DEFAULT: "tiiuae/falcon-7b",DownloadSource.MODELSCOPE: "AI-ModelScope/falcon-7b",},"Falcon-11B": {DownloadSource.DEFAULT: "tiiuae/falcon-11B",},"Falcon-40B": {DownloadSource.DEFAULT: "tiiuae/falcon-40b",DownloadSource.MODELSCOPE: "AI-ModelScope/falcon-40b",},"Falcon-180B": {DownloadSource.DEFAULT: "tiiuae/falcon-180b",DownloadSource.MODELSCOPE: "modelscope/falcon-180B",},"Falcon-7B-Chat": {DownloadSource.DEFAULT: "tiiuae/falcon-7b-instruct",DownloadSource.MODELSCOPE: "AI-ModelScope/falcon-7b-instruct",},"Falcon-40B-Chat": {DownloadSource.DEFAULT: "tiiuae/falcon-40b-instruct",DownloadSource.MODELSCOPE: "AI-ModelScope/falcon-40b-instruct",},"Falcon-180B-Chat": {DownloadSource.DEFAULT: "tiiuae/falcon-180b-chat",DownloadSource.MODELSCOPE: "modelscope/falcon-180B-chat",},},module="query_key_value",template="falcon",
)register_model_group(models={"Gemma-2B": {DownloadSource.DEFAULT: "google/gemma-2b",DownloadSource.MODELSCOPE: "AI-ModelScope/gemma-2b",},"Gemma-7B": {DownloadSource.DEFAULT: "google/gemma-7b",DownloadSource.MODELSCOPE: "AI-ModelScope/gemma-2b-it",},"Gemma-2B-Chat": {DownloadSource.DEFAULT: "google/gemma-2b-it",DownloadSource.MODELSCOPE: "AI-ModelScope/gemma-7b",},"Gemma-7B-Chat": {DownloadSource.DEFAULT: "google/gemma-7b-it",DownloadSource.MODELSCOPE: "AI-ModelScope/gemma-7b-it",},},template="gemma",
)register_model_group(models={"CodeGemma-2B": {DownloadSource.DEFAULT: "google/codegemma-1.1-2b",},"CodeGemma-7B": {DownloadSource.DEFAULT: "google/codegemma-7b",},"CodeGemma-7B-Chat": {DownloadSource.DEFAULT: "google/codegemma-1.1-7b-it",DownloadSource.MODELSCOPE: "AI-ModelScope/codegemma-7b-it",},},template="gemma",
)register_model_group(models={"InternLM-7B": {DownloadSource.DEFAULT: "internlm/internlm-7b",DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm-7b",},"InternLM-20B": {DownloadSource.DEFAULT: "internlm/internlm-20b",DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm-20b",},"InternLM-7B-Chat": {DownloadSource.DEFAULT: "internlm/internlm-chat-7b",DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm-chat-7b",},"InternLM-20B-Chat": {DownloadSource.DEFAULT: "internlm/internlm-chat-20b",DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm-chat-20b",},},template="intern",
)register_model_group(models={"InternLM2-7B": {DownloadSource.DEFAULT: "internlm/internlm2-7b",DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm2-7b",},"InternLM2-20B": {DownloadSource.DEFAULT: "internlm/internlm2-20b",DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm2-20b",},"InternLM2-7B-Chat": {DownloadSource.DEFAULT: "internlm/internlm2-chat-7b",DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm2-chat-7b",},"InternLM2-20B-Chat": {DownloadSource.DEFAULT: "internlm/internlm2-chat-20b",DownloadSource.MODELSCOPE: "Shanghai_AI_Laboratory/internlm2-chat-20b",},},module="wqkv",template="intern2",
)register_model_group(models={"Jambda-v0.1": {DownloadSource.DEFAULT: "ai21labs/Jamba-v0.1",DownloadSource.MODELSCOPE: "AI-ModelScope/Jamba-v0.1",}},
)register_model_group(models={"LingoWhale-8B": {DownloadSource.DEFAULT: "deeplang-ai/LingoWhale-8B",DownloadSource.MODELSCOPE: "DeepLang/LingoWhale-8B",}},module="qkv_proj",
)register_model_group(models={"LLaMA-7B": {DownloadSource.DEFAULT: "huggyllama/llama-7b",DownloadSource.MODELSCOPE: "skyline2006/llama-7b",},"LLaMA-13B": {DownloadSource.DEFAULT: "huggyllama/llama-13b",DownloadSource.MODELSCOPE: "skyline2006/llama-13b",},"LLaMA-30B": {DownloadSource.DEFAULT: "huggyllama/llama-30b",DownloadSource.MODELSCOPE: "skyline2006/llama-30b",},"LLaMA-65B": {DownloadSource.DEFAULT: "huggyllama/llama-65b",DownloadSource.MODELSCOPE: "skyline2006/llama-65b",},}
)register_model_group(models={"LLaMA2-7B": {DownloadSource.DEFAULT: "meta-llama/Llama-2-7b-hf",DownloadSource.MODELSCOPE: "modelscope/Llama-2-7b-ms",},"LLaMA2-13B": {DownloadSource.DEFAULT: "meta-llama/Llama-2-13b-hf",DownloadSource.MODELSCOPE: "modelscope/Llama-2-13b-ms",},"LLaMA2-70B": {DownloadSource.DEFAULT: "meta-llama/Llama-2-70b-hf",DownloadSource.MODELSCOPE: "modelscope/Llama-2-70b-ms",},"LLaMA2-7B-Chat": {DownloadSource.DEFAULT: "meta-llama/Llama-2-7b-chat-hf",DownloadSource.MODELSCOPE: "modelscope/Llama-2-7b-chat-ms",},"LLaMA2-13B-Chat": {DownloadSource.DEFAULT: "meta-llama/Llama-2-13b-chat-hf",DownloadSource.MODELSCOPE: "modelscope/Llama-2-13b-chat-ms",},"LLaMA2-70B-Chat": {DownloadSource.DEFAULT: "meta-llama/Llama-2-70b-chat-hf",DownloadSource.MODELSCOPE: "modelscope/Llama-2-70b-chat-ms",},},template="llama2",
)register_model_group(models={"LLaMA3-8B": {DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3-8B",DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3-8B",},"LLaMA3-70B": {DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3-70B",DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3-70B",},"LLaMA3-8B-Chat": {DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3-8B-Instruct",DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3-8B-Instruct",},"LLaMA3-70B-Chat": {DownloadSource.DEFAULT: "meta-llama/Meta-Llama-3-70B-Instruct",DownloadSource.MODELSCOPE: "LLM-Research/Meta-Llama-3-70B-Instruct",},"LLaMA3-8B-Chinese-Chat": {DownloadSource.DEFAULT: "shenzhi-wang/Llama3-8B-Chinese-Chat",DownloadSource.MODELSCOPE: "LLM-Research/Llama3-8B-Chinese-Chat",},"LLaMA3-70B-Chinese-Chat": {DownloadSource.DEFAULT: "shenzhi-wang/Llama3-70B-Chinese-Chat",},},template="llama3",
)register_model_group(models={"LLaVA1.5-7B-Chat": {DownloadSource.DEFAULT: "llava-hf/llava-1.5-7b-hf",},"LLaVA1.5-13B-Chat": {DownloadSource.DEFAULT: "llava-hf/llava-1.5-13b-hf",},},template="vicuna",vision=True,
)register_model_group(models={"Mistral-7B-v0.1": {DownloadSource.DEFAULT: "mistralai/Mistral-7B-v0.1",DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-v0.1",},"Mistral-7B-v0.1-Chat": {DownloadSource.DEFAULT: "mistralai/Mistral-7B-Instruct-v0.1",DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-Instruct-v0.1",},"Mistral-7B-v0.2": {DownloadSource.DEFAULT: "alpindale/Mistral-7B-v0.2-hf",DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-v0.2-hf",},"Mistral-7B-v0.2-Chat": {DownloadSource.DEFAULT: "mistralai/Mistral-7B-Instruct-v0.2",DownloadSource.MODELSCOPE: "AI-ModelScope/Mistral-7B-Instruct-v0.2",},},template="mistral",
)register_model_group(models={"Mixtral-8x7B-v0.1": {DownloadSource.DEFAULT: "mistralai/Mixtral-8x7B-v0.1",DownloadSource.MODELSCOPE: "AI-ModelScope/Mixtral-8x7B-v0.1",},"Mixtral-8x7B-v0.1-Chat": {DownloadSource.DEFAULT: "mistralai/Mixtral-8x7B-Instruct-v0.1",DownloadSource.MODELSCOPE: "AI-ModelScope/Mixtral-8x7B-Instruct-v0.1",},"Mixtral-8x22B-v0.1": {DownloadSource.DEFAULT: "mistralai/Mixtral-8x22B-v0.1",DownloadSource.MODELSCOPE: "AI-ModelScope/Mixtral-8x22B-v0.1",},"Mixtral-8x22B-v0.1-Chat": {DownloadSource.DEFAULT: "mistralai/Mixtral-8x22B-Instruct-v0.1",},},template="mistral",
)register_model_group(models={"OLMo-1B": {DownloadSource.DEFAULT: "allenai/OLMo-1B-hf",},"OLMo-7B": {DownloadSource.DEFAULT: "allenai/OLMo-7B-hf",},"OLMo-1.7-7B": {DownloadSource.DEFAULT: "allenai/OLMo-1.7-7B-hf",},},
)register_model_group(models={"OpenChat3.5-7B-Chat": {DownloadSource.DEFAULT: "openchat/openchat-3.5-0106",DownloadSource.MODELSCOPE: "xcwzxcwz/openchat-3.5-0106",}},template="openchat",
)register_model_group(models={"Orion-14B-Base": {DownloadSource.DEFAULT: "OrionStarAI/Orion-14B-Base",DownloadSource.MODELSCOPE: "OrionStarAI/Orion-14B-Base",},"Orion-14B-Chat": {DownloadSource.DEFAULT: "OrionStarAI/Orion-14B-Chat",DownloadSource.MODELSCOPE: "OrionStarAI/Orion-14B-Chat",},"Orion-14B-Long-Chat": {DownloadSource.DEFAULT: "OrionStarAI/Orion-14B-LongChat",DownloadSource.MODELSCOPE: "OrionStarAI/Orion-14B-LongChat",},"Orion-14B-RAG-Chat": {DownloadSource.DEFAULT: "OrionStarAI/Orion-14B-Chat-RAG",DownloadSource.MODELSCOPE: "OrionStarAI/Orion-14B-Chat-RAG",},"Orion-14B-Plugin-Chat": {DownloadSource.DEFAULT: "OrionStarAI/Orion-14B-Chat-Plugin",DownloadSource.MODELSCOPE: "OrionStarAI/Orion-14B-Chat-Plugin",},},template="orion",
)register_model_group(models={"PaliGemma-3B-pt-224": {DownloadSource.DEFAULT: "google/paligemma-3b-pt-224",},"PaliGemma-3B-pt-448": {DownloadSource.DEFAULT: "google/paligemma-3b-pt-448",},"PaliGemma-3B-pt-896": {DownloadSource.DEFAULT: "google/paligemma-3b-pt-896",},"PaliGemma-3B-mix-224": {DownloadSource.DEFAULT: "google/paligemma-3b-mix-224",},"PaliGemma-3B-mix-448": {DownloadSource.DEFAULT: "google/paligemma-3b-mix-448",},},vision=True,
)register_model_group(models={"Phi-1.5-1.3B": {DownloadSource.DEFAULT: "microsoft/phi-1_5",DownloadSource.MODELSCOPE: "allspace/PHI_1-5",},"Phi-2-2.7B": {DownloadSource.DEFAULT: "microsoft/phi-2",DownloadSource.MODELSCOPE: "AI-ModelScope/phi-2",},}
)register_model_group(models={"Phi3-3.8B-4k-Chat": {DownloadSource.DEFAULT: "microsoft/Phi-3-mini-4k-instruct",DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-mini-4k-instruct",},"Phi3-3.8B-128k-Chat": {DownloadSource.DEFAULT: "microsoft/Phi-3-mini-128k-instruct",DownloadSource.MODELSCOPE: "LLM-Research/Phi-3-mini-128k-instruct",},},module="qkv_proj",template="phi",
)register_model_group(models={"Qwen-1.8B": {DownloadSource.DEFAULT: "Qwen/Qwen-1_8B",DownloadSource.MODELSCOPE: "qwen/Qwen-1_8B",},"Qwen-7B": {DownloadSource.DEFAULT: "Qwen/Qwen-7B",DownloadSource.MODELSCOPE: "qwen/Qwen-7B",},"Qwen-14B": {DownloadSource.DEFAULT: "Qwen/Qwen-14B",DownloadSource.MODELSCOPE: "qwen/Qwen-14B",},"Qwen-72B": {DownloadSource.DEFAULT: "Qwen/Qwen-72B",DownloadSource.MODELSCOPE: "qwen/Qwen-72B",},"Qwen-1.8B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen-1_8B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen-1_8B-Chat",},"Qwen-7B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen-7B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen-7B-Chat",},"Qwen-14B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen-14B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen-14B-Chat",},"Qwen-72B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen-72B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen-72B-Chat",},"Qwen-1.8B-int8-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen-1_8B-Chat-Int8",DownloadSource.MODELSCOPE: "qwen/Qwen-1_8B-Chat-Int8",},"Qwen-1.8B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen-1_8B-Chat-Int4",DownloadSource.MODELSCOPE: "qwen/Qwen-1_8B-Chat-Int4",},"Qwen-7B-int8-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen-7B-Chat-Int8",DownloadSource.MODELSCOPE: "qwen/Qwen-7B-Chat-Int8",},"Qwen-7B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen-7B-Chat-Int4",DownloadSource.MODELSCOPE: "qwen/Qwen-7B-Chat-Int4",},"Qwen-14B-int8-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen-14B-Chat-Int8",DownloadSource.MODELSCOPE: "qwen/Qwen-14B-Chat-Int8",},"Qwen-14B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen-14B-Chat-Int4",DownloadSource.MODELSCOPE: "qwen/Qwen-14B-Chat-Int4",},"Qwen-72B-int8-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen-72B-Chat-Int8",DownloadSource.MODELSCOPE: "qwen/Qwen-72B-Chat-Int8",},"Qwen-72B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen-72B-Chat-Int4",DownloadSource.MODELSCOPE: "qwen/Qwen-72B-Chat-Int4",},},module="c_attn",template="qwen",
)register_model_group(models={"Qwen1.5-0.5B": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-0.5B",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-0.5B",},"Qwen1.5-1.8B": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-1.8B",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-1.8B",},"Qwen1.5-4B": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-4B",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-4B",},"Qwen1.5-7B": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-7B",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-7B",},"Qwen1.5-14B": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-14B",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-14B",},"Qwen1.5-32B": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-32B",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-32B",},"Qwen1.5-72B": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-72B",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-72B",},"Qwen1.5-110B": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-110B",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-110B",},"Qwen1.5-MoE-A2.7B": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-MoE-A2.7B",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-MoE-A2.7B",},"Qwen1.5-Code-7B": {DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B",DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B",},"Qwen1.5-0.5B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-0.5B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-0.5B-Chat",},"Qwen1.5-1.8B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-1.8B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-1.8B-Chat",},"Qwen1.5-4B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-4B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-4B-Chat",},"Qwen1.5-7B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-7B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-7B-Chat",},"Qwen1.5-14B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-14B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-14B-Chat",},"Qwen1.5-32B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-32B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-32B-Chat",},"Qwen1.5-72B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-72B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-72B-Chat",},"Qwen1.5-110B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-110B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-110B-Chat",},"Qwen1.5-MoE-A2.7B-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-MoE-A2.7B-Chat",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-MoE-A2.7B-Chat",},"Qwen1.5-Code-7B-Chat": {DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B-Chat",DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B-Chat",},"Qwen1.5-0.5B-int8-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-0.5B-Chat-GPTQ-Int8",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-0.5B-Chat-GPTQ-Int8",},"Qwen1.5-0.5B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-0.5B-Chat-AWQ",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-0.5B-Chat-AWQ",},"Qwen1.5-1.8B-int8-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-1.8B-Chat-GPTQ-Int8",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-1.8B-Chat-GPTQ-Int8",},"Qwen1.5-1.8B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-1.8B-Chat-AWQ",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-1.8B-Chat-AWQ",},"Qwen1.5-4B-int8-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-4B-Chat-GPTQ-Int8",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-4B-Chat-GPTQ-Int8",},"Qwen1.5-4B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-4B-Chat-AWQ",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-4B-Chat-AWQ",},"Qwen1.5-7B-int8-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-7B-Chat-GPTQ-Int8",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-7B-Chat-GPTQ-Int8",},"Qwen1.5-7B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-7B-Chat-AWQ",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-7B-Chat-AWQ",},"Qwen1.5-14B-int8-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-14B-Chat-GPTQ-Int8",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-14B-Chat-GPTQ-Int8",},"Qwen1.5-14B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-14B-Chat-AWQ",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-14B-Chat-AWQ",},"Qwen1.5-32B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-32B-Chat-AWQ",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-32B-Chat-AWQ",},"Qwen1.5-72B-int8-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-72B-Chat-GPTQ-Int8",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-72B-Chat-GPTQ-Int8",},"Qwen1.5-72B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-72B-Chat-AWQ",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-72B-Chat-AWQ",},"Qwen1.5-110B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-110B-Chat-AWQ",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-110B-Chat-AWQ",},"Qwen1.5-MoE-A2.7B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4",DownloadSource.MODELSCOPE: "qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4",},"Qwen1.5-Code-7B-int4-Chat": {DownloadSource.DEFAULT: "Qwen/CodeQwen1.5-7B-Chat-AWQ",DownloadSource.MODELSCOPE: "qwen/CodeQwen1.5-7B-Chat-AWQ",},},template="qwen",
)register_model_group(models={"SOLAR-10.7B": {DownloadSource.DEFAULT: "upstage/SOLAR-10.7B-v1.0",},"SOLAR-10.7B-Chat": {DownloadSource.DEFAULT: "upstage/SOLAR-10.7B-Instruct-v1.0",DownloadSource.MODELSCOPE: "AI-ModelScope/SOLAR-10.7B-Instruct-v1.0",},},template="solar",
)register_model_group(models={"Skywork-13B-Base": {DownloadSource.DEFAULT: "Skywork/Skywork-13B-base",DownloadSource.MODELSCOPE: "skywork/Skywork-13B-base",}}
)register_model_group(models={"StarCoder2-3B": {DownloadSource.DEFAULT: "bigcode/starcoder2-3b",DownloadSource.MODELSCOPE: "AI-ModelScope/starcoder2-3b",},"StarCoder2-7B": {DownloadSource.DEFAULT: "bigcode/starcoder2-7b",DownloadSource.MODELSCOPE: "AI-ModelScope/starcoder2-7b",},"StarCoder2-15B": {DownloadSource.DEFAULT: "bigcode/starcoder2-15b",DownloadSource.MODELSCOPE: "AI-ModelScope/starcoder2-15b",},}
)register_model_group(models={"Vicuna1.5-7B-Chat": {DownloadSource.DEFAULT: "lmsys/vicuna-7b-v1.5",DownloadSource.MODELSCOPE: "Xorbits/vicuna-7b-v1.5",},"Vicuna1.5-13B-Chat": {DownloadSource.DEFAULT: "lmsys/vicuna-13b-v1.5",DownloadSource.MODELSCOPE: "Xorbits/vicuna-13b-v1.5",},},template="vicuna",
)register_model_group(models={"XuanYuan-6B": {DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-6B",DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-6B",},"XuanYuan-70B": {DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-70B",DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-70B",},"XuanYuan-2-70B": {DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan2-70B",DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan2-70B",},"XuanYuan-6B-Chat": {DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-6B-Chat",DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-6B-Chat",},"XuanYuan-70B-Chat": {DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-70B-Chat",DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-70B-Chat",},"XuanYuan-2-70B-Chat": {DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan2-70B-Chat",DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan2-70B-Chat",},"XuanYuan-6B-int8-Chat": {DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-6B-Chat-8bit",DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-6B-Chat-8bit",},"XuanYuan-6B-int4-Chat": {DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-6B-Chat-4bit",DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-6B-Chat-4bit",},"XuanYuan-70B-int8-Chat": {DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-70B-Chat-8bit",DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-70B-Chat-8bit",},"XuanYuan-70B-int4-Chat": {DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan-70B-Chat-4bit",DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan-70B-Chat-4bit",},"XuanYuan-2-70B-int8-Chat": {DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan2-70B-Chat-8bit",DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan2-70B-Chat-8bit",},"XuanYuan-2-70B-int4-Chat": {DownloadSource.DEFAULT: "Duxiaoman-DI/XuanYuan2-70B-Chat-4bit",DownloadSource.MODELSCOPE: "Duxiaoman-DI/XuanYuan2-70B-Chat-4bit",},},template="xuanyuan",
)register_model_group(models={"XVERSE-7B": {DownloadSource.DEFAULT: "xverse/XVERSE-7B",DownloadSource.MODELSCOPE: "xverse/XVERSE-7B",},"XVERSE-13B": {DownloadSource.DEFAULT: "xverse/XVERSE-13B",DownloadSource.MODELSCOPE: "xverse/XVERSE-13B",},"XVERSE-65B": {DownloadSource.DEFAULT: "xverse/XVERSE-65B",DownloadSource.MODELSCOPE: "xverse/XVERSE-65B",},"XVERSE-65B-2": {DownloadSource.DEFAULT: "xverse/XVERSE-65B-2",DownloadSource.MODELSCOPE: "xverse/XVERSE-65B-2",},"XVERSE-7B-Chat": {DownloadSource.DEFAULT: "xverse/XVERSE-7B-Chat",DownloadSource.MODELSCOPE: "xverse/XVERSE-7B-Chat",},"XVERSE-13B-Chat": {DownloadSource.DEFAULT: "xverse/XVERSE-13B-Chat",DownloadSource.MODELSCOPE: "xverse/XVERSE-13B-Chat",},"XVERSE-65B-Chat": {DownloadSource.DEFAULT: "xverse/XVERSE-65B-Chat",DownloadSource.MODELSCOPE: "xverse/XVERSE-65B-Chat",},"XVERSE-MoE-A4.2B": {DownloadSource.DEFAULT: "xverse/XVERSE-MoE-A4.2B",DownloadSource.MODELSCOPE: "xverse/XVERSE-MoE-A4.2B",},"XVERSE-7B-int8-Chat": {DownloadSource.DEFAULT: "xverse/XVERSE-7B-Chat-GPTQ-Int8",DownloadSource.MODELSCOPE: "xverse/XVERSE-7B-Chat-GPTQ-Int8",},"XVERSE-7B-int4-Chat": {DownloadSource.DEFAULT: "xverse/XVERSE-7B-Chat-GPTQ-Int4",DownloadSource.MODELSCOPE: "xverse/XVERSE-7B-Chat-GPTQ-Int4",},"XVERSE-13B-int8-Chat": {DownloadSource.DEFAULT: "xverse/XVERSE-13B-Chat-GPTQ-Int8",DownloadSource.MODELSCOPE: "xverse/XVERSE-13B-Chat-GPTQ-Int8",},"XVERSE-13B-int4-Chat": {DownloadSource.DEFAULT: "xverse/XVERSE-13B-Chat-GPTQ-Int4",DownloadSource.MODELSCOPE: "xverse/XVERSE-13B-Chat-GPTQ-Int4",},"XVERSE-65B-int4-Chat": {DownloadSource.DEFAULT: "xverse/XVERSE-65B-Chat-GPTQ-Int4",DownloadSource.MODELSCOPE: "xverse/XVERSE-65B-Chat-GPTQ-Int4",},},template="xverse",
)register_model_group(models={"Yayi-7B": {DownloadSource.DEFAULT: "wenge-research/yayi-7b-llama2",DownloadSource.MODELSCOPE: "AI-ModelScope/yayi-7b-llama2",},"Yayi-13B": {DownloadSource.DEFAULT: "wenge-research/yayi-13b-llama2",DownloadSource.MODELSCOPE: "AI-ModelScope/yayi-13b-llama2",},},template="yayi",
)register_model_group(models={"Yi-6B": {DownloadSource.DEFAULT: "01-ai/Yi-6B",DownloadSource.MODELSCOPE: "01ai/Yi-6B",},"Yi-9B": {DownloadSource.DEFAULT: "01-ai/Yi-9B",DownloadSource.MODELSCOPE: "01ai/Yi-9B",},"Yi-34B": {DownloadSource.DEFAULT: "01-ai/Yi-34B",DownloadSource.MODELSCOPE: "01ai/Yi-34B",},"Yi-6B-Chat": {DownloadSource.DEFAULT: "01-ai/Yi-6B-Chat",DownloadSource.MODELSCOPE: "01ai/Yi-6B-Chat",},"Yi-34B-Chat": {DownloadSource.DEFAULT: "01-ai/Yi-34B-Chat",DownloadSource.MODELSCOPE: "01ai/Yi-34B-Chat",},"Yi-6B-int8-Chat": {DownloadSource.DEFAULT: "01-ai/Yi-6B-Chat-8bits",DownloadSource.MODELSCOPE: "01ai/Yi-6B-Chat-8bits",},"Yi-6B-int4-Chat": {DownloadSource.DEFAULT: "01-ai/Yi-6B-Chat-4bits",DownloadSource.MODELSCOPE: "01ai/Yi-6B-Chat-4bits",},"Yi-34B-int8-Chat": {DownloadSource.DEFAULT: "01-ai/Yi-34B-Chat-8bits",DownloadSource.MODELSCOPE: "01ai/Yi-34B-Chat-8bits",},"Yi-34B-int4-Chat": {DownloadSource.DEFAULT: "01-ai/Yi-34B-Chat-4bits",DownloadSource.MODELSCOPE: "01ai/Yi-34B-Chat-4bits",},"Yi-1.5-6B": {DownloadSource.DEFAULT: "01-ai/Yi-1.5-6B",DownloadSource.MODELSCOPE: "01ai/Yi-1.5-6B",},"Yi-1.5-9B": {DownloadSource.DEFAULT: "01-ai/Yi-1.5-9B",DownloadSource.MODELSCOPE: "01ai/Yi-1.5-9B",},"Yi-1.5-34B": {DownloadSource.DEFAULT: "01-ai/Yi-1.5-34B",DownloadSource.MODELSCOPE: "01ai/Yi-1.5-34B",},"Yi-1.5-6B-Chat": {DownloadSource.DEFAULT: "01-ai/Yi-1.5-6B-Chat",DownloadSource.MODELSCOPE: "01ai/Yi-1.5-6B-Chat",},"Yi-1.5-9B-Chat": {DownloadSource.DEFAULT: "01-ai/Yi-1.5-9B-Chat",DownloadSource.MODELSCOPE: "01ai/Yi-1.5-9B-Chat",},"Yi-1.5-34B-Chat": {DownloadSource.DEFAULT: "01-ai/Yi-1.5-34B-Chat",DownloadSource.MODELSCOPE: "01ai/Yi-1.5-34B-Chat",},},template="yi",
)register_model_group(models={"YiVL-6B-Chat": {DownloadSource.DEFAULT: "BUAADreamer/Yi-VL-6B-hf",},"YiVL-34B-Chat": {DownloadSource.DEFAULT: "BUAADreamer/Yi-VL-34B-hf",},},template="yi_vl",vision=True,
)register_model_group(models={"Yuan2-2B-Chat": {DownloadSource.DEFAULT: "IEITYuan/Yuan2-2B-hf",DownloadSource.MODELSCOPE: "YuanLLM/Yuan2.0-2B-hf",},"Yuan2-51B-Chat": {DownloadSource.DEFAULT: "IEITYuan/Yuan2-51B-hf",DownloadSource.MODELSCOPE: "YuanLLM/Yuan2.0-51B-hf",},"Yuan2-102B-Chat": {DownloadSource.DEFAULT: "IEITYuan/Yuan2-102B-hf",DownloadSource.MODELSCOPE: "YuanLLM/Yuan2.0-102B-hf",},},template="yuan",
)register_model_group(models={"Zephyr-7B-Alpha-Chat": {DownloadSource.DEFAULT: "HuggingFaceH4/zephyr-7b-alpha",DownloadSource.MODELSCOPE: "AI-ModelScope/zephyr-7b-alpha",},"Zephyr-7B-Beta-Chat": {DownloadSource.DEFAULT: "HuggingFaceH4/zephyr-7b-beta",DownloadSource.MODELSCOPE: "modelscope/zephyr-7b-beta",},"Zephyr-141B-ORPO-Chat": {DownloadSource.DEFAULT: "HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1",},},template="zephyr",
)

代码中提到的大型模型名称包括：

1. Baichuan-7B-Base
2. Baichuan-13B-Base
3. Baichuan-13B-Chat
4. Baichuan2-7B-Base
5. Baichuan2-13B-Base
6. Baichuan2-7B-Chat
7. Baichuan2-13B-Chat
8. BLOOM-560M
9. BLOOM-3B
10. BLOOM-7B1
11. BLOOMZ-560M
12. BLOOMZ-3B
13. BLOOMZ-7B1-mt
14. BlueLM-7B-Base
15. BlueLM-7B-Chat
16. Breeze-7B
17. Breeze-7B-Chat
18. ChatGLM2-6B-Chat
19. ChatGLM3-6B-Base
20. ChatGLM3-6B-Chat
21. ChineseLLaMA2-1.3B
22. ChineseLLaMA2-7B
23. ChineseLLaMA2-13B
24. ChineseLLaMA2-1.3B-Chat
25. ChineseLLaMA2-7B-Chat
26. ChineseLLaMA2-13B-Chat
27. CommandR-35B-Chat
28. CommandR-Plus-104B-Chat
29. CommandR-35B-4bit-Chat
30. CommandR-Plus-104B-4bit-Chat
31. DBRX-132B-Base
32. DBRX-132B-Chat
33. DeepSeek-LLM-7B-Base
34. DeepSeek-LLM-67B-Base
35. DeepSeek-LLM-7B-Chat
36. DeepSeek-LLM-67B-Chat
37. DeepSeek-Math-7B-Base
38. DeepSeek-Math-7B-Chat
39. DeepSeek-MoE-16B-Base
40. DeepSeek-MoE-16B-v2-Base
41. DeepSeek-MoE-236B-Base
42. DeepSeek-MoE-16B-Chat
43. DeepSeek-MoE-16B-v2-Chat
44. DeepSeek-MoE-236B-Chat
45. DeepSeekCoder-6.7B-Base
46. DeepSeekCoder-7B-Base
47. DeepSeekCoder-33B-Base
48. DeepSeekCoder-6.7B-Chat
49. DeepSeekCoder-7B-Chat
50. DeepSeekCoder-33B-Chat
51. Falcon-7B
52. Falcon-11B
53. Falcon-40B
54. Falcon-180B
55. Falcon-7B-Chat
56. Falcon-40B-Chat
57. Falcon-180B-Chat
58. Gemma-2B
59. Gemma-7B
60. Gemma-2B-Chat
61. Gemma-7B-Chat
62. CodeGemma-2B
63. CodeGemma-7B
64. CodeGemma-7B-Chat
65. InternLM-7B
66. InternLM-20B
67. InternLM-7B-Chat
68. InternLM-20B-Chat
69. InternLM2-7B
70. InternLM2-20B
71. InternLM2-7B-Chat
72. InternLM2-20B-Chat
73. Jambda-v0.1
74. LingoWhale-8B
75. LLaMA-7B
76. LLaMA-13B
77. LLaMA-30B
78. LLaMA-65B
79. LLaMA2-7B
80. LLaMA2-13B
81. LLaMA2-70B
82. LLaMA2-7B-Chat
83. LLaMA2-13B-Chat
84. LLaMA2-70B-Chat
85. LLaMA3-8B
86. LLaMA3-70B
87. LLaMA3-8B-Chat
88. LLaMA3-70B-Chat
89. LLaMA3-8B-Chinese-Chat
90. LLaMA3-70B-Chinese-Chat
91. LLaVA1.5-7B-Chat
92. LLaVA1.5-13B-Chat
93. Mistral-7B-v0.1
94. Mistral-7B-v0.1-Chat
95. Mistral-7B-v0.2
96. Mistral-7B-v0.2-Chat
97. Mixtral-8x7B-v0.1
98. Mixtral-8x7B-v0.1-Chat
99. Mixtral-8x22B-v0.1
100. Mixtral-8x22B-v0.1-Chat
101. OLMo-1B
102. OLMo-7B
103. OLMo-1.7-7B
104. OpenChat3.5-7B-Chat
105. Orion-14B-Base
106. Orion-14B-Chat
107. Orion-14B-Long-Chat
108. Orion-14B-RAG-Chat
109. Orion-14B-Plugin-Chat
110. PaliGemma-3B-pt-224
111. PaliGemma-3B-pt-448
112. PaliGemma-3B-pt-896
113. PaliGemma-3B-mix-224
114. PaliGemma-3B-mix-448
115. Phi-1.5-1.3B
116. Phi-2-2.7B
117. Phi3-3.8B-4k-Chat
118. Phi3-3.8B-128k-Chat
119. Qwen-1.8B
120. Qwen-7B
121. Qwen-14B
122. Qwen-72B
123. Qwen-1.8B-Chat
124. Qwen-7B-Chat
125. Qwen-14B-Chat
126. Qwen-72B-Chat
127. Qwen-1.8B-int8-Chat
128. Qwen-1.8B-int4-Chat
129. Qwen-7B-int8-Chat
130. Qwen-7B-int4-Chat
131. Qwen-14B-int8-Chat
132. Qwen-14B-int4-Chat
133. Qwen-72B-int8-Chat
134. Qwen-72B-int4-Chat
135. Qwen1.5-0.5B
136. Qwen1.5-1.8B
137. Qwen1.5-4B
138. Qwen1.5-7B
139. Qwen1.5-14B
140. Qwen1.5-32B
141. Qwen1.5-72B
142. Qwen1.5-110B
143. Qwen1.5-MoE-A2.7B
144. Qwen1.5-Code-7B
145. Qwen1.5-0.5B-Chat
146. Qwen1.5-1.8B-Chat
147. Qwen1.5-4B-Chat
148. Qwen1.5-7B-Chat
149. Qwen1.5-14B-Chat
150. Qwen1.5-32B-Chat
151. Qwen1.5-72B-Chat
152. Qwen1.5-110B-Chat
153. Qwen1.5-MoE-A2.7B-Chat
154. Qwen1.5-Code-7B-Chat
155. Qwen1.5-0.5B-int8-Chat
156. Qwen1.5-0.5B-int4-Chat
157. Qwen1.5-1.8B-int8-Chat
158. Qwen1.5-1.8B-int4-Chat
159. Qwen1.5-4B-int8-Chat
160. Qwen1.5-4B-int4-Chat
161. Qwen1.5-7B-int8-Chat
162. Qwen1.5-7B-int4-Chat
163. Qwen1.5-14B-int8-Chat
164. Qwen1.5-14B-int4-Chat
165. Qwen1.5-32B-int4-Chat
166. Qwen1.5-72B-int8-Chat
167. Qwen1.5-72B-int4-Chat
168. Qwen1.5-110B-int4-Chat
169. Qwen1.5-MoE-A2.7B-int4-Chat
170. Qwen1.5-Code-7B-int4-Chat
171. SOLAR-10.7B
172. SOLAR-10.7B-Chat
173. Skywork-13B-Base
174. StarCoder2-3B
175. StarCoder2-7B
176. StarCoder2-15B
177. Vicuna1.5-7B-Chat
178. Vicuna1.5-13B-Chat
179. XuanYuan-6B
180. XuanYuan-70B
181. XuanYuan-2-70B
182. XuanYuan-6B-Chat
183. XuanYuan-70B-Chat
184. XuanYuan-2-70B-Chat
185. XuanYuan-6B-int8-Chat
186. XuanYuan-6B-int4-Chat
187. XuanYuan-70B-int8-Chat
188. XuanYuan-70B-int4-Chat
189. XuanYuan-2-70B-int8-Chat
190. XuanYuan-2-70B-int4-Chat
191. XVERSE-7B
192. XVERSE-13B
193. XVERSE-65B
194. XVERSE-65B-2
195. XVERSE-7B-Chat
196. XVERSE-13B-Chat
197. XVERSE-65B-Chat
198. XVERSE-MoE-A4.2B
199. XVERSE-7B-int8-Chat
200. XVERSE-7B-int4-Chat
201. XVERSE-13B-int8-Chat
202. XVERSE-13B-int4-Chat
203. XVERSE-65B-int4-Chat
204. Yayi-7B
205. Yayi-13B
206. Yi-6B
207. Yi-9B
208. Yi-34B
209. Yi-6B-Chat
210. Yi-34B-Chat
211. Yi-6B-int8-Chat
212. Yi-6B-int4-Chat
213. Yi-34B-int8-Chat
214. Yi-34B-int4-Chat
215. Yi-1.5-6B
216. Yi-1.5-9B
217. Yi-1.5-34B
218. Yi-1.5-6B-Chat
219. Yi-1.5-9B-Chat
220. Yi-1.5-34B-Chat
221. YiVL-6B-Chat
222. YiVL-34B-Chat
223. Yuan2-2B-Chat
224. Yuan2-51B-Chat
225. Yuan2-102B-Chat
226. Zephyr-7B-Alpha-Chat
227. Zephyr-7B-Beta-Chat
228. Zephyr-141B-ORPO-Chat

大模型技术分享

《企业级生成式人工智能LLM大模型技术、算法及案例实战》线上高级研修讲座

模块一：Generative AI 原理本质、技术内核及工程实践周期详解
模块二：工业级 Prompting 技术内幕及端到端的基于LLM 的会议助理实战
模块三：三大 Llama 2 模型详解及实战构建安全可靠的智能对话系统
模块四：生产环境下 GenAI/LLMs 的五大核心问题及构建健壮的应用实战
模块五：大模型应用开发技术：Agentic-based 应用技术及案例实战
模块六：LLM 大模型微调及模型 Quantization 技术及案例实战
模块七：大模型高效微调 PEFT 算法、技术、流程及代码实战进阶
模块八：LLM 模型对齐技术、流程及进行文本Toxicity 分析实战
模块九：构建安全的 GenAI/LLMs 核心技术Red Teaming 解密实战
模块十：构建可信赖的企业私有安全大模型Responsible AI 实战 

Llama3关键技术深度解析与构建Responsible AI、算法及开发落地实战

1、Llama开源模型家族大模型技术、工具和多模态详解：学员将深入了解Meta Llama 3的创新之处，比如其在语言模型技术上的突破，并学习到如何在Llama 3中构建trust and safety AI。他们将详细了解Llama 3的五大技术分支及工具，以及如何在AWS上实战Llama指令微调的案例。
2、解密Llama 3 Foundation Model模型结构特色技术及代码实现：深入了解Llama 3中的各种技术，比如Tiktokenizer、KV Cache、Grouped Multi-Query Attention等。通过项目二逐行剖析Llama 3的源码，加深对技术的理解。
3、解密Llama 3 Foundation Model模型结构核心技术及代码实现：SwiGLU Activation Function、FeedForward Block、Encoder Block等。通过项目三学习Llama 3的推理及Inferencing代码，加强对技术的实践理解。
4、基于LangGraph on Llama 3构建Responsible AI实战体验：通过项目四在Llama 3上实战基于LangGraph的Responsible AI项目。他们将了解到LangGraph的三大核心组件、运行机制和流程步骤，从而加强对Responsible AI的实践能力。
5、Llama模型家族构建技术构建安全可信赖企业级AI应用内幕详解：深入了解构建安全可靠的企业级AI应用所需的关键技术，比如Code Llama、Llama Guard等。项目五实战构建安全可靠的对话智能项目升级版，加强对安全性的实践理解。
6、Llama模型家族Fine-tuning技术与算法实战：学员将学习Fine-tuning技术与算法，比如Supervised Fine-Tuning(SFT)、Reward Model技术、PPO算法、DPO算法等。项目六动手实现PPO及DPO算法，加强对算法的理解和应用能力。
7、Llama模型家族基于AI反馈的强化学习技术解密：深入学习Llama模型家族基于AI反馈的强化学习技术，比如RLAIF和RLHF。项目七实战基于RLAIF的Constitutional AI。
8、Llama 3中的DPO原理、算法、组件及具体实现及算法进阶：学习Llama 3中结合使用PPO和DPO算法，剖析DPO的原理和工作机制，详细解析DPO中的关键算法组件，并通过综合项目八从零开始动手实现和测试DPO算法，同时课程将解密DPO进阶技术Iterative DPO及IPO算法。
9、Llama模型家族Safety设计与实现：在这个模块中，学员将学习Llama模型家族的Safety设计与实现，比如Safety in Pretraining、Safety Fine-Tuning等。构建安全可靠的GenAI/LLMs项目开发。
10、Llama 3构建可信赖的企业私有安全大模型Responsible AI系统：构建可信赖的企业私有安全大模型Responsible AI系统，掌握Llama 3的Constitutional AI、Red Teaming。

解码Sora架构、技术及应用

一、为何Sora通往AGI道路的里程碑？
1，探索从大规模语言模型(LLM)到大规模视觉模型(LVM)的关键转变，揭示其在实现通用人工智能(AGI)中的作用。
2，展示Visual Data和Text Data结合的成功案例，解析Sora在此过程中扮演的关键角色。
3，详细介绍Sora如何依据文本指令生成具有三维一致性(3D consistency)的视频内容。 4，解析Sora如何根据图像或视频生成高保真内容的技术路径。
5，探讨Sora在不同应用场景中的实践价值及其面临的挑战和局限性。

二、解码Sora架构原理
1，DiT (Diffusion Transformer)架构详解
2，DiT是如何帮助Sora实现Consistent、Realistic、Imaginative视频内容的？
3，探讨为何选用Transformer作为Diffusion的核心网络，而非技术如U-Net。
4，DiT的Patchification原理及流程，揭示其在处理视频和图像数据中的重要性。
5，Conditional Diffusion过程详解，及其在内容生成过程中的作用。
三、解码Sora关键技术解密
1，Sora如何利用Transformer和Diffusion技术理解物体间的互动，及其对模拟复杂互动场景的重要性。
2，为何说Space-time patches是Sora技术的核心，及其对视频生成能力的提升作用。
3，Spacetime latent patches详解，探讨其在视频压缩和生成中的关键角色。
4，Sora Simulator如何利用Space-time patches构建digital和physical世界，及其对模拟真实世界变化的能力。
5，Sora如何实现faithfully按照用户输入文本而生成内容，探讨背后的技术与创新。
6，Sora为何依据abstract concept而不是依据具体的pixels进行内容生成，及其对模型生成质量与多样性的影响。