HuggingFace Accelerated Downloads

Use internal acceleration nodes for fast HuggingFace model downloads

Overview

SynpixCloud GPU instances include built-in HuggingFace acceleration nodes that provide internal high-speed transfers, improving download speeds by 100x or more. Large models that would take hours to download can now be completed in just minutes.

Quick Setup

Run the following command in your GPU instance terminal to enable accelerated downloads:

export HF_ENDPOINT=http://192.168.50.202:18090

After configuration, use huggingface-cli to download models:

huggingface-cli download deepseek-ai/DeepSeek-R1

Permanent Configuration

Add the environment variable to ~/.bashrc for persistent configuration:

echo 'export HF_ENDPOINT=http://192.168.50.202:18090' >> ~/.bashrc
source ~/.bashrc

Using in Python Code

Set the environment variable in your Python code:

import os
os.environ['HF_ENDPOINT'] = 'http://192.168.50.202:18090'

from transformers import AutoModel, AutoTokenizer

# Downloads will now automatically use the acceleration node
model = AutoModel.from_pretrained("bert-base-uncased")
tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")

Pre-cached Model Repository

We have pre-cached some popular models for even faster downloads. Use this configuration:

export HF_ENDPOINT="http://guest:guest@223.109.239.18:20281/repository/hf/"
export HF_HUB_ENABLE_HF_TRANSFER=0
export HF_HUB_ENABLE_HF_XET=1
export HF_HUB_DOWNLOAD_TIMEOUT=120
export HF_HUB_ETAG_TIMEOUT=1800

Available Cached Models

Browse all cached models at the Model Repository.

Some cached models include:

ModelDescription
Qwen/Qwen3-235B-A22BQwen3 large language model
meta-llama/Llama-4-Scout-17B-16EMeta Llama 4
black-forest-labs/FLUX.1-devFLUX.1 image generation
google/gemma-3-27b-itGoogle Gemma 3
deepseek-ai/DeepSeek-R1DeepSeek R1 reasoning model

Speed Comparison

ConfigurationDownload SpeedRecommendation
HuggingFace Official~125 KB/sNot recommended
hf-mirror.com Public Mirror~3 MB/sAlternative
Internal Acceleration Node50+ MB/sRecommended

The internal acceleration node is only available within SynpixCloud GPU instances. For external access, use the public address: http://223.109.239.18:18090

Troubleshooting

Download Failed?

  1. Verify the environment variable is set correctly: echo $HF_ENDPOINT
  2. Check network connectivity: ping 192.168.50.202
  3. Try downloading again

How to Verify Acceleration is Working?

Download a small model to test:

time huggingface-cli download bert-base-uncased config.json

If configured correctly, the download should complete in seconds.

Support

Need help? Contact us at support@synpixcloud.com