The HuggingFace Model Downloader is a utility tool for downloading models/datasets from the HuggingFace website. It provides multithreaded downloading capabilities for LFS files and ensures the integrity of the downloaded models by checking their SHA256 checksum.

Git LFS was so slow for me, and I cloudn't find a single binary that I can just run to download any model. In addition, this might be integrated later in my future projects for inference using golang/python combination

the script will download the correct version based on os/arch and save the binary as "hfdownloader" in the same folder

bash <(curl -sSL https://g.bodaay.io/hfd) -h

to install it to default OS bin folder

bash <(curl -sSL https://g.bodaay.io/hfd) -i

it will automatically request higher 'sudo' previlages if required, you can specify the install destination by adding -p

bash <(curl -sSL https://g.bodaay.io/hfd) -i -p ~/.local/bin/

the bash script will just download the binary based on your os/arch and run it

Download Model: TheBloke/orca_mini_7B-GPTQ

bash <(curl -sSL https://g.bodaay.io/hfd) -m TheBloke/orca_mini_7B-GPTQ

Download Model: TheBloke/vicuna-13b-v1.3.0-GGML and get GGML Variant: q4_0

bash <(curl -sSL https://g.bodaay.io/hfd) -m TheBloke/vicuna-13b-v1.3.0-GGML:q4_0

Download Model: TheBloke/vicuna-13b-v1.3.0-GGML and get GGML Variants: q4_0,q5_0, and save each one in a separate folder

bash <(curl -sSL https://g.bodaay.io/hfd) -f -m TheBloke/vicuna-13b-v1.3.0-GGML:q4_0,q5_0

Download Model: TheBloke/vicuna-13b-v1.3.0-GGML and save them into /workspace/, 8 connections and get GGML Variant: q4_0,q4_K_S

bash <(curl -sSL https://g.bodaay.io/hfd) -m TheBloke/vicuna-13b-v1.3.0-GGML:q4_0,q4_K_S -c 8 -s /workspace/

hfdowloader [flags]

-m, --model string
Model/Dataset name (required if dataset not set)

You can supply filters for required LFS model files, separate filters by adding commas

filters will discard any LFS file ending with .bin,.act,.safetensors,.zip thats missing the supplied filtercd out

-m TheBloke/WizardLM-Uncensored-Falcon-7B-GGML:fp16 # this will download LFS file contains: fp16

-m TheBloke/WizardLM-33B-V1.0-Uncensored-GGML:q4_K_S,q5_K_M # this will download LFS file contains: q4_K_S  or  q5_K_M

-d, --dataset string
Model/Dataset name (required if model not set)

-f, --appendFilterFolder bool
Append the filter name to the folder, use it for GGML ONLY qunatizatized filterd download only (optional)

 # this will download LFS file contains: q4_K_S  or  q5_K_M, in a separate folders by appending the filder name to model folder name
 # all other non-lfs files and not ending with one of these extension: .bin,.safetensors,.meta,.zip will be availale in each folder
-f -m TheBloke/WizardLM-33B-V1.0-Uncensored-GGML:q4_K_S,q5_K_M

-k, --skipSHA bool
SKip SHA256 checking for LFS files, usefull when trying to resum interrupted download and complet missing files quickly (optional)

-b, --branch string
Model/Dataset branch (optional) (default "main")

-s, --storage string
Storage path (optional) (default "Storage")

-c, --concurrent int
Number of LFS concurrent connections (optional) (default 5)

-t, --token string
HuggingFace Access Token, this can be automatically supplied by env variable 'HUGGING_FACE_HUB_TOKEN' or .env file (recommended), required for some Models/Datasets, you still need to manually accept agreement if model requires it (optional)

-i, --install bool
Install the binary to the OS default bin folder (if installPath not specified), Unix-like operating systems only

-p, --installPath string
used with -i to copy the binary to spceified path, default to: /usr/local/bin/ (optional)

-h, --help
Help for hfdowloader

Model Example

hfdowloader  -m TheBloke/WizardLM-13B-V1.0-Uncensored-GPTQ -c 10 -s MyModels

Dataset Example

hfdowloader  -d facebook/flores -c 10 -s MyDatasets

• Nested File Downloading of the Model
• Multithreaded downloading of large files (LFS)
• Filter Downloads, specic LFS models files can be specified for downloading (Usefull for GGMLs), saving time and space
• Simple utlity that can used as library easily or just a single binary, all functionality in one go file and can be imported in any project
• SHA256 checksum verification for LFS downloaded models
• Skipping previsouly downloaded files
• Resume progress for Interrupted downloads for LFS files
• Simple File size matching for non-LFS files
• Support HuggingFace Access Token, for restricted models/datasets