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docs: enhance CLI demo documentation

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OleehyO 2025-01-16 09:34:52 +00:00
parent bf9c351a10
commit bf73742c05
1 changed files with 7 additions and 2 deletions
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inference/cli_demo.py
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@ -14,7 +14,10 @@ To run the script, use the following command with appropriate arguments:
$ python cli_demo.py --prompt "A girl riding a bike." --model_path THUDM/CogVideoX1.5-5b --generate_type "t2v" $ python cli_demo.py --prompt "A girl riding a bike." --model_path THUDM/CogVideoX1.5-5b --generate_type "t2v"
``` ```
You can change `pipe.enable_sequential_cpu_offload()` to `pipe.enable_model_cpu_offload()` to speed up inference, but this will use more GPU memory
Additional options are available to specify the model path, guidance scale, number of inference steps, video generation type, and output paths. Additional options are available to specify the model path, guidance scale, number of inference steps, video generation type, and output paths.
""" """
import argparse import argparse
@ -22,6 +25,7 @@ import logging
from typing import Literal, Optional from typing import Literal, Optional
import torch import torch
from diffusers import ( from diffusers import (
CogVideoXDPMScheduler, CogVideoXDPMScheduler,
CogVideoXImageToVideoPipeline, CogVideoXImageToVideoPipeline,
@ -134,8 +138,9 @@ def generate_video(
# 3. Enable CPU offload for the model. # 3. Enable CPU offload for the model.
# turn off if you have multiple GPUs or enough GPU memory(such as H100) and it will cost less time in inference # turn off if you have multiple GPUs or enough GPU memory(such as H100) and it will cost less time in inference
# and enable to("cuda") # and enable to("cuda")
# pipe.to("cuda") # pipe.to("cuda")
# pipe.enable_model_cpu_offload()
pipe.enable_sequential_cpu_offload() pipe.enable_sequential_cpu_offload()
pipe.vae.enable_slicing() pipe.vae.enable_slicing()
pipe.vae.enable_tiling() pipe.vae.enable_tiling()