Huggingface download speed. We would like to show you a description here but the site won’t allow us. The performance of model The problem is that, now I have to use git clone to download the model with command line in the linux server, however even if I use HuggingFace-cli and my token, the speed is still less than 500k/s, Just a small tool to make it easier to download specific files from huggingface or to limit the download speed. from datasets. However, I then tried picking some I work on Hugging Face's Xet team and we're intensely focused on speeding up uploads and downloads with a chunk-based approach to deduplication (leveraging a Rust client and content This guide offers step-by-step instructions on how to speed up and improve the reliability of your Hugging Face downloads using two powerful This bandwidth test measures your connection speed to Hugging Face's servers by downloading a sample file. You can also integrate this into your own library. 0 do I need to rename or put somewhere ?! I don't have enough time to It balances accuracy, speed, and model size, making it ideal for both server-side and edge deployment. As a new user, you’re Download + preparation speed of datasets. Use Direct Download or Mirror Sources Hugging Face models are stored as Git repositories with Large File Storage (LFS), which can cause issues if Git LFS isn’t HuggingFace-Download-Accelerator是一个专为国内用户开发的HuggingFace资源下载工具。该项目结合官方下载工具和镜像站，大幅提升了模型和数据集的下载速度。它支持自定义存储路径、授权模型获 Because i want to read large data, it is very slow to access full data with huggingface dataset. 6 huggingface_hub = 0. cache\huggingface\hub and is there the model I should put models--stabilityai--stable-diffusion-xl-base-1. co, I tried to use huggingface-cli download file. Topic Replies Views Activity The download of a model is too slow Beginners 0 7826 September 2, 2023 Model downloading speed too low Models 4 776 November 21, 2024 Spikes on I am trying to download model using git-lfs on jarvislabs. Then go directly to the extract step, because the compressed Hi, What optimizations would you recommend for increasing model download speeds from Hugging Face? from datasets import load_dataset dataset = load_dataset(“imagenet-1k”, split = “train”) I have seen that the above code downloads the data in partitions . Includes comparison tables, links to the best research resources, and real 🚀 Introducing MCP-HuggingFetch: The High-Speed HuggingFace Model Downloader Ever been frustrated waiting forever for large AI models to Counting the number of downloads for models is not a trivial task, as a single model repository might contain multiple files, including multiple model weight files (e. However, I noticed once command Here’s a structured approach: 1. For example, downloading a 17B parameter In general to make an intelligent decision about how much download we should accommodate if we want CI jobs to be faster, we need to know an average download speed - which Run Qwen3-Coder-480B-A35B-Instruct: To achieve inference speeds of 6+ tokens per second for our 1-bit quant, we recommend at least 150GB of unified memory (combined VRAM and RAM) or 150GB of This first download using just git and git lfs was served to me at an average speed of 100 MiB/s. I get an average download speed of 2. 4 Reproduction We have not been able to reproduce and it is hard to really give details, since it happens very rarely in a system that Download a very large dataset Hello, I want to upload a very large dataset to the hub, and would like to make sure that users are able to efficiently download it. 1. I know that when I upload it, it Did others also notice a significant slow-down in download speeds? I’m getting around 10MB/s, which really messes up my workflow (where I’m downloading into virtual machines). 5 MB/s. Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. There is a constant in huggingface_hub called HF_TRANSFER_CONCURRENCY. I know the folder is here : . Do you know what causes Wasn't even aware you can use hf_transfer for something other than downloading models from Huggingface. I checked network speed but I do not know the reason. 400-600 Kb/sec . 50 Mbps and it If you are running on a machine with high bandwidth, you can speed up downloads by allowing hf_xet to run on all CPU cores. download_manager import DownloadManager dl_manager = DownloadManager Downloading llm (10GB+) through the HuggingFace Hub is terrible as the current single-threaded downloader is extremely slow and inefficient. ai Speed is terribly slow. However, I noticed once command Performance analysis Following up on speed comments in #689 I made a more systematic test to see the download speed using Repository and git clone. This marks our zero We’re on a journey to advance and democratize artificial intelligence through open source and open science. co/models, but can't find a 'Download' link. It simplifies access to machine learning System Info hf_transfer = 0. Because of 🚀 Introducing MCP-HuggingFetch: The High-Speed HuggingFace Model Downloader Ever been frustrated waiting forever for large AI models to I noticed that basically every model I try to download on the most liked page was getting these speeds. Are you guys able to download stable Why This Tool? Parallel Downloads Maximize your bandwidth with multiple connections per file and concurrent file downloads: Up to 16 parallel connections This application helps you test your internet bandwidth to check your connection speed. cache/huggingface #13941 Closed This below code works but it is just slow How can i speed up? Machine has much bigger speed and i really need to download lots of AI models to test Thank you import os import requests Considering the lack of multi-threaded download support in the official huggingface-cli, and the inadequate error handling in hf_transfer, This command-line tool leverages curl and aria2c For example, I want to download bert-base-uncased on https://huggingface. For example: huggingface-cli download --downrate 8M To limit I want to download a HuggingFace dataset, e. You can login using your huggingface. I would like to know why this happens. Progress bars are working locally, on Colab and in Spaces which are the main use The huggingface_hub library provides functions to download files from the repositories stored on the Hub. For the longest time, running a model locally felt like something that required a research My internet speed is not good, so I can only accept single-threading. Downloading via HF CLI (with XET enabled) is usually faster than using a browser, though it’s rare for browser downloads to be significantly slow It’s possible your ISP or network route is When downloading a model, huggingface-cli opens many connections and completely maxes out the connection's bandwidth. load_dataset is 20x slower than huggingface hub snapshot and manual loding #6439 I download my data from huggingface by DownloadManager. , Cohere Transcribe currently ranks #1 for accuracy on HuggingFace’s Open ASR Leaderboard, setting a new benchmark for real-world transcription performance. com and hf. g. In download. I also added load_dataset for completeness A command line flag that would allow you to set the maximum download speed. I switched to cpu only instance so hat It wouldnt cost me. The test calculates: For accurate results, close other bandwidth-intensive applications Hi, What optimizations would you recommend for increasing model download speeds from Hugging Face? See the CLI download documentation for more information. . I think the only way would be to monkey patch it before calling the upload/download function. it will also download files one by one instead of the whole repository at once if Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. You can use these functions independently or integrate them into your own library, making it First time installing any AI model and I’m basically just following a simple guide to get stable diffusion 1. It's just a tool that multiplexes the Can't tell why specifically on Kaggle the progress bar doesn't work but not sure we will spent much time investigating it. We’re on a journey to advance and democratize artificial intelligence through open source and open science. Let's set HF_HUB_ENABLE_HF_TRANSFER=1 in the search/worker env template maybe ? And we also Asking because in this case it would be useful for the benchmark section to compare download speed using plain huggingface_hub (as already I am getting this too, but its not limited to popular models, my speeds start around 10 mB/s then drop down to 500 kB/s. Dear fellow Spark users, I’m currently experimenting with vLLM (and a few other apps on my DGX Spark). Whenever I try to download safetensors or other files from Hugging Face, the download I use VPN (specifically ShadowRocket) to access huggingface. 28kB/s). The model has three main variants optimized for specific I know the folder is here : . It is comparable to the Test results can be found in the outputs directory, which by default includes two folders for transformers and vllm, storing test results for HuggingFace transformers and vLLM respectively. You can use these functions independently or integrate them into your own library, making it I download clip with transformers-cli download openai/clip-vit-base-patch32 but the speed is too slow (3. Qwen releases Qwen3-Coder-Next, an 80B MoE model (3B active parameters) with 256K context for fast agentic coding and local use. Here's the Exact Workflow. git` folder, which This guide offers step-by-step instructions on how to speed up and improve the reliability of your Hugging Face downloads using two powerful Hi everyone! 👋 I am trying to download the Falcon-7B model from its repo into my local machine and the download speed is very slow. Upon cancelling and restarting the download i get a speed burst again. uonlp/CulturaX: from datasets import load_dataset ds = load_dataset ("uonlp/CulturaX", "en") However, it downloads on one thread at 50 We would like to show you a description here but the site won’t allow us. Or is it not huggingface-cli [hf_xet] error and low download speed (on slow residential connection) #3036 Closed aa956 opened on Apr 28, 2025 HF Transfer is a high-performance file transfer library designed to speed up downloads from and uploads to the Hugging Face Hub. I want to know wmt download speed example #525 Closed sshleifer opened this issue on Aug 21, 2020 · 8 comments Contributor Since this dataset is 16 TB, I'd prefer to download it faster so that I don't have to wait for a few days. For example, gemma-2-2b takes a lot of time to download. Download the pretrained checkpoints: First, make sure you have installed the huggingface CLI and modelscope CLI. py the code sets hf_transfer The official RealRestorer repo requires a patched fork of diffusers that will break existing ComfyUI environments. This node pack reimplements the full pipeline from scratch using only standard Efficiently downloads HuggingFace models by circumventing the `. It can speed up the download process by approximately 2x by avoiding downloading the `. hf_xet is a Rust-based package We’re on a journey to advance and democratize artificial intelligence through open source and open science. 0 do I need to rename or put somewhere ?! I don't have enough time to When using load_dataset(), each download of the dataset will end in 10 minutes, even if the download has not yet been completed. If your model download is too slow and fails, you can manually download it from our S3 using your browser, wget or cURL as an alternative A practical guide to decoding LLM model names — what B, IT, GGUF, Q4_K_M, MoE, and every other suffix means. This page documents the function The huggingface_hub library provides functions to download files from the repositories stored on the Hub. For example, if we tried to download the Pile in its entirety, we’d need 825 GB of free disk space! To handle these cases, 🤗 Datasets provides a streaming feature that allows us to download and access We’re on a journey to advance and democratize artificial intelligence through open source and open science. This forum is powered by Discourse and relies on a trust-level system. git` directory. ai, using two available methods: Glows. The default 8 threads downloading simultaneously is too much, causing frequent interruptions and download failures. download. ai Datadrive storage (local download and upload), and instance-based High-speed image editing with compact Flux 2 Klein models, now supported in ComfyUI. 5. 21. As a new user, you’re temporarily limited in the number of topics So setting the environment variable after the import may have no effect. It would work with small huggingface_hub streams each download in small chunks and appends them to a temp file, and because the file keeps growing incrementally, Windows keeps adding each new bit of data The download function is a core API component of hf_transfer, providing high-performance parallel file downloads with resilient error handling. co credentials. I want to know 摘要： 本文详细分析2026年HuggingFace模型下载慢和ConnectionError的常见原因，提供了基于国内镜像和hf. It provides a Rust implementation with Python bindings Contribute to huggingface/hf_transfer development by creating an account on GitHub. The HuggingFace Model Downloader is a utility tool designed to streamline the process of downloading models and datasets from the HuggingFace platform. First time installing any AI model and I’m basically just following a simple guide to get stable diffusion 1. Continuous disconnect and failed downloads. I Downloaded a HuggingFace Model and Ran It Locally in 10 Minutes. It is very fast. co缓存的完整解决方案。 文章包含详细的配置步骤、代码示例、性能对比表格以及自动化缓 Unless I missed it, there's no concurrency here, despite the common practice of model weights being large and sharded, and therefore a prime target for speedup by concurrent/parallel Pretrained model download slowly，It will speed up when I delete the folder $USER/. Simply open the app, and it will provide you with the results showing I download clip with transformers-cli download openai/clip-vit-base-patch32 but the speed is too slow (3. You have to pip install hf_transfer and then run your script with This tutorial explains how to download HuggingFace models on Glows. Would like to isolate whether you're I am trying to install stable diffusion onto my computer but I simply can't download large files onto my computers. That is extremely fast, and I was surprised given that I was downloading about 30 GiB of data When experiencing slow or failing downloads of Sentence Transformer models from Hugging Face, there are several strategies you can employ to mitigate these issues. How can I multithreadedly download a HuggingFace dataset? You can login using your huggingface. Describe the bug Example case This server has over 1 Gbit download speed If i start multiple files fetch all combined reaches 300 megabytes per second + lets say repo has 10 files so Bug description Sometimes the download speed is pretty slow, no more than 10. How can I just download the first Also if possible anymore detailed info about the slower speeds you are seeing compared to other similar downloaders like the python version. For example, you can quickly load a Scikit-learn model to maximize download speed on a big machine, you can use hf_transfer which is specifically dedicated to this. cu9i ra5p 6xhv aef xqwa jag oksw 3gkc ewa a7j djdz thtj fdi7 sl5m oifc qbv gwy uns6 kh3 fuvv h7d eati dksq fxt m8rg 7f2t duc knzm ayo ldou