'timed out waiting for llama runner to start' in ~6 minutes when trying to load large model

I'm trying to send a query to LLM with the following code:

from ollama import Client, Options
from datetime import datetime

model_name = 'llama3.1:70b-instruct-q8_0'
client = Client(host='https://llama.my.server.com', timeout=360000)
pull_result = client.pull(model_name)

response = client.chat(
    # keep_alive=0,
    model=model_name,
    messages=[
        {"role": "user", "content": f"$myPrompt"},
    ],
    options=Options(
        # num_ctx=128000,
        num_ctx=64000,
        use_mmap=True,
        keep_alive=0,
        timeout=360000
    )
)

print("Model responce: ", response['response'])

The error I'm getting is ollama._types.ResponseError: timed out waiting for llama runner to start - progress 1.00 -
On the server it's Aug 8 22:19:19 myserver ollama[2197083]: time=2024-08-08T22:19:19.371+02:00 level=ERROR source=sched.go:451 msg="error loading llama server" error="timed out waiting for llama runner to start - progress 1.00 - "

To be fair - it's quite a stretch for the server - with 64GB RAM (+huge swap), 8 vCPUs (4 real cores, I believe) and no GPU, but I'm fine to wait a few hours if required, especially, since I configured time-outs, or at least I believe so - based on the examples and issues I've found here.

Any help would be much appreciated!

Start by reproducing the timeout with the Python Client and Options configuration shown, using the reported model and server settings. Trace how the client timeout and model-loading timeout are handled, including the server log location sched.go:451. Done means the timeout behavior is understood and the issue has a confirmed fix or documented limitation.