GitLab

Switch ARM64 container image base to rocky 8

The centos 7 arm mirrors have disappeared due to the EOL 2 days
ago, and the vault sed workaround which works for x86 doesn't work for arm.

Centos 7 EOL broke mirrors

As of July 1st 2024: Could not resolve host: mirrorlist.centos.org
This is expected due to EOL dates.

fix: trim spaces for FROM argument, don't trim inside of quotes

fix: add unsupported architecture message for linux/windows

Fix case for NumCtx

Document concurrent behavior and settings

This may confuse users thinking "auto" is an acceptable string - it must be numeric

Enable concurrency by default

* Update README.md

Added Mesop example to web & desktop

* Update README.md

---------
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

Runs fine on a NVIDIA GeForce GTX 1050 Ti

* Do not shift context for sliding window models

* truncate prompt > 2/3 tokens

* only target gemma2

* Check exists projtype

* Maintain Ordering

gemma2 graph

* update readme for gemma 2

Previously, some costly things were causing the loading of GGUF files
and their metadata and tensor information to be VERY slow:

  * Too many allocations when decoding strings
  * Hitting disk for each read of each key and value, resulting in a
    not-okay amount of syscalls/disk I/O.

The show API is now down to 33ms from 800ms+ for llama3 on a macbook pro
m3.

This commit also prevents collecting large arrays of values when
decoding GGUFs (if desired). When such keys are encountered, their
values are null, and are encoded as such in JSON.

Also, this fixes a broken test that was not encoding valid GGUF.

This commit changes the 'ollama run' command to defer fetching model
information until it really needs it. That is, when in interactive mode.

It also removes one such case where the model information is fetch in
duplicate, just before calling generateInteractive and then again, first
thing, in generateInteractive.

This positively impacts the performance of the command:

    ; time ./before run llama3 'hi'
    Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat?

    ./before run llama3 'hi'  0.02s user 0.01s system 2% cpu 1.168 total
    ; time ./before run llama3 'hi'
    Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat?

    ./before run llama3 'hi'  0.02s user 0.01s system 2% cpu 1.220 total
    ; time ./before run llama3 'hi'
    Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat?

    ./before run llama3 'hi'  0.02s user 0.01s system 2% cpu 1.217 total
    ; time ./after run llama3 'hi'
    Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat?

    ./after run llama3 'hi'  0.02s user 0.01s system 4% cpu 0.652 total
    ; time ./after run llama3 'hi'
    Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat?

    ./after run llama3 'hi'  0.01s user 0.01s system 5% cpu 0.498 total
    ; time ./after run llama3 'hi'
    Hi! It's nice to meet you. Is there something I can help you with or would you like to chat?

    ./after run llama3 'hi'  0.01s user 0.01s system 3% cpu 0.479 total
    ; time ./after run llama3 'hi'
    Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat?

    ./after run llama3 'hi'  0.02s user 0.01s system 5% cpu 0.507 total
    ; time ./after run llama3 'hi'
    Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat?

    ./after run llama3 'hi'  0.02s user 0.01s system 5% cpu 0.507 total

Fix use_mmap parsing for modelfiles

Provide consistent ordering for the ps command - longest duration listed first

Until ROCm v6.2 ships, we wont be able to get accurate free memory
reporting on windows, which makes automatic concurrency too risky.
Users can still opt-in but will need to pay attention to model sizes otherwise they may thrash/page VRAM or cause OOM crashes.
All other platforms and GPUs have accurate VRAM reporting wired
up now, so we can turn on concurrency by default.

This adjusts our default settings to enable multiple models and parallel
requests to a single model.  Users can still override these by the same
env var settings as before.  Parallel has a direct impact on
num_ctx, which in turn can have a significant impact on small VRAM GPUs
so this change also refines the algorithm so that when parallel is not
explicitly set by the user, we try to find a reasonable default that fits
the model on their GPU(s).  As before, multiple models will only load
concurrently if they fully fit in VRAM.

fix: quantization with template

Add the new tristate parsing logic for the code path for modelfiles,
as well as a unit test.

Refine mmap default logic on linux