Skip to content

Latest commit

 

History

History
82 lines (59 loc) · 3.23 KB

README.md

File metadata and controls

82 lines (59 loc) · 3.23 KB

Download Pretrained Models

All models are stored in HunyuanVideo-I2V/ckpts by default, and the file structure is as follows

HunyuanVideo-I2V
  ├──ckpts
  │  ├──README.md
  │  ├──hunyuan-video-i2v-720p
  │  │  ├──transformers
  │  │  │  ├──mp_rank_00_model_states.pt
  ├  │  ├──vae
  ├  │  ├──lora
  │  │  │  ├──embrace_kohaya_weights.safetensors
  │  │  │  ├──hair_growth_kohaya_weights.safetensors
  │  ├──text_encoder_i2v
  │  ├──text_encoder_2
  ├──...

Download HunyuanVideo-I2V model

To download the HunyuanVideo-I2V model, first install the huggingface-cli. (Detailed instructions are available here.)

python -m pip install "huggingface_hub[cli]"

Then download the model using the following commands:

# Switch to the directory named 'HunyuanVideo-I2V'
cd HunyuanVideo-I2V
# Use the huggingface-cli tool to download HunyuanVideo-I2V model in HunyuanVideo-I2V/ckpts dir.
# The download time may vary from 10 minutes to 1 hour depending on network conditions.
huggingface-cli download tencent/HunyuanVideo-I2V --local-dir ./ckpts
💡Tips for using huggingface-cli (network problem)
1. Using HF-Mirror

If you encounter slow download speeds in China, you can try a mirror to speed up the download process. For example,

HF_ENDPOINT=https://hf-mirror.com huggingface-cli download tencent/HunyuanVideo-I2V --local-dir ./ckpts
2. Resume Download

huggingface-cli supports resuming downloads. If the download is interrupted, you can just rerun the download command to resume the download process.

Note: If an No such file or directory: 'ckpts/.huggingface/.gitignore.lock' like error occurs during the download process, you can ignore the error and rerun the download command.

Download Text Encoder

HunyuanVideo-I2V uses an MLLM model and a CLIP model as text encoder.

  1. MLLM model (text_encoder_i2v folder)

HunyuanVideo-I2V supports different MLLMs (including HunyuanMLLM and open-source MLLM models). At this stage, we have not yet released HunyuanMLLM. We recommend the user in community to use llava-llama-3-8b provided by Xtuer, which can be downloaded by the following command.

Note that unlike HunyuanVideo, which only uses the language model parts of llava-llama-3-8b-v1_1-transformers, HunyuanVideo-I2V needs its full model to encode both prompts and images. Therefore, you only need to download the model without preprocessing.

cd HunyuanVideo-I2V/ckpts
huggingface-cli download xtuner/llava-llama-3-8b-v1_1-transformers --local-dir ./text_encoder_i2v
  1. CLIP model (text_encoder_2 folder)

We use CLIP provided by OpenAI as another text encoder, users in the community can download this model by the following command

cd HunyuanVideo-I2V/ckpts
huggingface-cli download openai/clip-vit-large-patch14 --local-dir ./text_encoder_2