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

2024-05-23 20:52
文章标签 语言 使用 训练 模型 微调 简介 factory llama tuning supervised fine 家族 sft

本文主要是介绍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，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

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

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微调大模型可以像这样轻松…

Llama-factory

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。

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  • 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。

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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

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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

在这里插入图片描述

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《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。

这篇关于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简介的文章就介绍到这儿，希望我们推荐的文章对编程师们有所帮助！


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