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Originally created by @nexon33 on GitHub (Jan 13, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/8406
What is the issue?
The raspberry pi 5 is connected over wifi but this shouldn't be a problem since my other device pulls the models correctly on the same wifi.
Suggested fix: I currently have to constantly cancel the downloads with CTRL + C, this saves the download state and then continues where it left off, functioning as some kind of save/checkpoint. Maybe its possible to backup the download state once in a while so that it doesn't stop downloading on a crash?
Feel free to request more info or let me know if you want me to test!
Edit: sometimes the error "Error: context canceled" shows up and I think it might be related
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0.5.4
@rick-github commented on GitHub (Jan 13, 2025):
It's not clear to me what problem you are having. If a download (
ollama pullorollama run) is interrupted, it should restart from the point of interruption the next time you runollama pull. The exception is if you reboot the server - when it starts, the server does some housecleaning which includes clearing failed downloads. So if you interrupt a download but want to continue it later, don't restart the server.@nexon33 commented on GitHub (Jan 13, 2025):
The problem is that the state is saved only when interrupted manually, not when it crashes during the download.
@rick-github commented on GitHub (Jan 13, 2025):
Pulling a model shouldn't crash the server. Can you provide more info?
@rick-github commented on GitHub (Jan 13, 2025):
Server logs might help.
@nexon33 commented on GitHub (Jan 14, 2025):
The server is not crashing but there are errors in the backend, I will try once more when I get home this evening
@cjuerg67 commented on GitHub (Jan 14, 2025):
I have the same issue on a RPi4 (4 GB), connected via LAN. The download (after run or pull) gets to about 10%, then stops, and after some seconds starts again with 0%. Looking now how to copy (via WinSCP) the same model from the Windows PC, where it works flawless.
@ACertainArchangel commented on GitHub (Jan 15, 2025):
This control C thing you came up with is brilliant! Exactly what I needed. Thanks.
@rick-github commented on GitHub (Jan 15, 2025):
The "control C thing" is a fine workaround but doesn't fix the problem. for which server logs might be helpful.
@cjuerg67 commented on GitHub (Jan 15, 2025):
This repeats again and again. What else could help to solve the problem?
@cjuerg67 commented on GitHub (Jan 15, 2025):
Switched on debug mode and restarted ollama, but I guess no new information...
@rick-github commented on GitHub (Jan 15, 2025):
Background: https://github.com/ollama/ollama/issues/8330#issuecomment-2574510267
What's the load on the pi5 during download? Can you get a measure of bandwidth saturation on the network link? If other machines on your LAN can download models, it could be that the pi5 is choking it's own download either due to network congestion, CPU overload or disk bandwidth. The parellelization of the download might just be too much. Unfortunately there are currently no knobs to control the download, the only workarounds at the moment are the "control C thing" or copying the models off another machine.
@rick-github commented on GitHub (Jan 15, 2025):
Something else to try: downgrade to an older version and try the pull. I haven't checked, but something may have changed in the download code to make it more sensitive to stalls on low power machines.
@rick-github commented on GitHub (Jan 15, 2025):
Are specific models causing a problem?
@cjuerg67 commented on GitHub (Jan 15, 2025):
Same problem with qwen:0.5b.
I guess it's related to the slow SD card writing. As I said, I'm using a pi4. Today I get a pi5 with nvme SSD :-)
Now that llama3.2 works, I see that I need a more powerful system...
And using ctrl-c is really a workaround. But you have to use it immediately after observing a decreasing download rate, otherwise you fall back to the last successful point - which is 0% at the beginning. After a ctr-c I wait till the green LED turns off (as it seems to show sd-card access?), and then start the pull again.
In that way I was able to download llama3.2:3b with about 13x ctrl-c.
@cjuerg67 commented on GitHub (Jan 15, 2025):
With ollama 0.4.0, download works!
(But llama3.1 does not: Error: model requires more system memory (6.2 GiB) than is available (3.7 GiB) - but that's another problem...)
@cjuerg67 commented on GitHub (Jan 15, 2025):
And the RPi5 with 8GB and 128 GB NVMe SSD which just arrived has no problems when downloading models with ollama 0.5.5
@ACertainArchangel commented on GitHub (Jan 15, 2025):
I'm really interested to see if this gets solved. Even if it's not a solution it would be fun to see if there is a way to script "the control c thing" with kill, ollama pull, and a while loop. I'll look into it when I have some more time. Maybe something like this:
I'll try running it with a new model tonight.
@ACertainArchangel commented on GitHub (Jan 16, 2025):
It works!
@andreagrandi commented on GitHub (Jan 25, 2025):
I'm on MacOS and using Ollama 0.5.7 and I have the same bug. I start pulling a model, it downloads 4% or 5%, then it resets and goes back to 0%. This is what I see in the logs:
just for info, my Mac is an M2 Pro with 32 GB RAM and over 500 GB of disk space still available
@rick-github commented on GitHub (Jan 25, 2025):
The stall detector is deleting stalled blob chunks. It's not clear if this is a problem with the Cloudfare CDN or something in-between. I just pulled deepseek-r1:8b without any problems but I'm likely hitting a different part of the CDN than you. Until it's resolved you can try this script to pull a model.
@dazistgut commented on GitHub (Jan 25, 2025):
If your environment is Windows, the following worked for me: https://github.com/dazistgut/ollamapullloop-win/tree/main
@DuskyElf commented on GitHub (Feb 1, 2025):
I made literally the exact same script, this is the weirdest bug I've seen in a while. I really want it to be solved tho.
@gordan-bobic commented on GitHub (Feb 3, 2025):
Same bug here, pulls often abort for no obvious reason (plenty of disk space, no memory shortage)
Ollama version: 0.5.7
Platform: x86-64, non-AVX (built from source for non-AVX, minimal patches, mostly just build flags for gcc/go)
Was not experiencing this problem with Ollama 0.3.14.
@rick-github commented on GitHub (Feb 3, 2025):
The reason is likely in the server logs.
@gordan-bobic commented on GitHub (Feb 3, 2025):
So this looks like the ollama daemon actually crashed.
The manual abort (before it spontaneously happens) workaround with pulls resuming where they left off, works.
@rick-github commented on GitHub (Feb 3, 2025):
https://github.com/ollama/ollama/issues/8400
@gordan-bobic commented on GitHub (Feb 3, 2025):
It may be the same bug, but I'm not using a proxy.
@rick-github commented on GitHub (Feb 3, 2025):
Yeah, the first report was from somebody using a proxy, but it's clear that's not the cause. There's a PR under review.
@jufo commented on GitHub (Feb 8, 2025):
I am seeing this on a Raspberry Pi 5 16GB with NVME SSD, tethered to a mobile phone with flaky Internet. I see the same problem to a lesser extent on a MacBook pro using the same wireless hotspot. The error in the logs is as posted earlier;
Feb 08 16:51:58 p15-1 ollama[31623]: time=2025-02-08T16:51:58.175Z level=INFO source=download.go:370 msg="29d8c98fa6b0 part 9 stalled; retrying. If this persists, press ctrl-c to exit, then 'ollama pull' to find a faster connection."I see that the relevant code was changed 3 days ago, to increase a timeout there from 5s to 30s. It is still a hard-coded "magic number" - it would be better to externalise parameters like this so people with poor connectivity could tweak them.
https://github.com/ollama/ollama/blob/main/server/download.go
yashwanth2706
server: increase timeout in stall detection from 5s to 30s (#8831)
@jufo commented on GitHub (Feb 10, 2025):
I am on version 0.5.7. The script posted in the "Failsafe model download" issue (#8535) works well for me.
The notable (and extremely frustrating) feature of the download behaviour in 0.5.7 is the progress bar advancing and then falling back... and then falling back further, sometimes all the way to zero.
At work I have access to Enterprise ChatGPT - see the attached Markdown file for a conversation I had about how the current code could cause progress to go backwards.
ChatGPT Coding Assistant on Ollama download code.md
@rick-github commented on GitHub (Mar 4, 2025):
This should be mitigated as of 0.5.8 by #8831 and #9294 provides an overhaul of model pulling, so closing but feel free to add updates if you are still having issues.