Wan2.1 I2V 14B 480P gguf
简介
核心亮点
- 图生视频能力强,画面动态自然且稳定
- GGUF 量化大幅降低显存,适配消费级显卡
- 支持 480P 分辨率,兼顾生成速度与质量
- Apache-2.0 协议,商业使用灵活无压力
使用方法
# 安装 Hugging Face transformers
pip install transformers torch
# 使用 transformers 加载模型
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("city96/Wan2.1-I2V-14B-480P-gguf")
tokenizer = AutoTokenizer.from_pretrained("city96/Wan2.1-I2V-14B-480P-gguf")
Hugging Face 下载
我们推荐使用命令行或者 Hugging Face Hub SDK 来进行模型的下载。
操作指引:在下载前,请先通过如下命令安装 huggingface_hub:
pip install -U huggingface_hub
命令行下载
下载完整模型库
huggingface-cli download city96/Wan2.1-I2V-14B-480P-gguf
下载单个文件到指定本地文件夹(以下载 config.json 到当前路径下 ./dir 目录为例)
huggingface-cli download city96/Wan2.1-I2V-14B-480P-gguf config.json --local-dir ./dir
SDK 下载
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('city96/Wan2.1-I2V-14B-480P-gguf')
Git 下载
请确保 lfs 已经被正确安装
git lfs install
git clone https://huggingface.co/city96/Wan2.1-I2V-14B-480P-gguf
如果您希望跳过 lfs 大文件下载,可以使用如下命令
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/city96/Wan2.1-I2V-14B-480P-gguf
模型文件托管在 Hugging Face Hub,使用 HF CLI / SDK / Git 直接下载,不经过本站。
PyTorch / Transformers 使用
安装 Transformers
pip install -U transformers torch
模型加载和推理
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained('city96/Wan2.1-I2V-14B-480P-gguf')
tokenizer = AutoTokenizer.from_pretrained('city96/Wan2.1-I2V-14B-480P-gguf')
模型下载
我们推荐使用命令行或者 ModelScope SDK 来进行模型的下载。
操作指引:在下载前,请先通过如下命令安装 ModelScope:
pip install modelscope
命令行下载
下载完整模型库
modelscope download --model city96/Wan2.1-I2V-14B-480P-gguf
下载单个文件到指定本地文件夹(以下载 README.md 到当前路径下 dir 目录为例)
modelscope download --model city96/Wan2.1-I2V-14B-480P-gguf README.md --local_dir ./dir
SDK 下载
# 模型下载
from modelscope import snapshot_download
model_dir = snapshot_download('city96/Wan2.1-I2V-14B-480P-gguf')
Git 下载
请确保 lfs 已经被正确安装
git lfs install
git clone https://www.modelscope.cn/city96/Wan2.1-I2V-14B-480P-gguf.git
如果您希望跳过 lfs 大文件下载,可以使用如下命令
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/city96/Wan2.1-I2V-14B-480P-gguf.git
ModelScope 模型页直接下载模型文件;无需将模型文件放在本站服务器。
Notebook 快速开发
下载并安装 ModelScope library
pip install "modelscope[audio,cv,nlp,multi-modal,science]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
模型加载和推理
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
p = pipeline('text-generation', 'city96/Wan2.1-I2V-14B-480P-gguf')
完整文档
---
base_model: Wan-AI/Wan2.1-I2V-14B-480P
library_name: gguf
quantized_by: city96
tags:
- video
- video-generation
license: apache-2.0
pipeline_tag: image-to-video
language:
- en
- zh
---
This is a direct GGUF conversion of Wan-AI/Wan2.1-I2V-14B-480P
All quants are created from the FP32 base file, though I only uploaded FP16 due to it exceeding the 50GB max file limit and gguf-split loading not currently being supported in ComfyUI-GGUF.
The model files can be used with the ComfyUI-GGUF custom node.
Place model files in ComfyUI/models/unet - see the GitHub readme for further install instructions.
The other files required can be downloaded from this repository by Comfy-Org
Please refer to this chart for a basic overview of quantization types.