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 fixes some brittle, simple equality checks to use errors.Is. Since
go1.13, errors.Is is the idiomatic way to check for errors.
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
* select layers based on estimated model memory usage
* always account for scratch vram
* dont load +1 layers
* better estmation for graph alloc
* Update gpu/gpu_darwin.go
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
* Update llm/llm.go
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
* Update llm/llm.go
* add overhead for cuda memory
* Update llm/llm.go
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
* fix build error on linux
* address comments
---------
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
ggufv3 adds support for big endianness, mainly for s390x architecture.
while that's not currently supported for ollama, the change is simple.
loosen version check to be more forward compatible. unless specified,
gguf versions other v1 will be decoded into v2.
* remove tmp directories created by previous servers
* clean up on server stop
* Update routes.go
* Update server/routes.go
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
* create top-level temp ollama dir
* check file exists before creating
---------
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
Co-authored-by: Michael Yang <mxyng@pm.me>
* subprocess improvements
- increase start-up timeout
- when runner fails to start fail rather than timing out
- try runners in order rather than choosing 1 runner
- embed metal runner in metal dir rather than gpu
- refactor logging and error messages
* Update llama.go
* Update llama.go
* simplify by using glob
