* readme: add Ellama to list of community integrations (#9800)
* readme: add screenpipe to community integrations (#9786)
* Add support for ROCm gfx1151 (#9773)
* conditionally enable parallel pipelines
* sample: make mutations in transforms explicit (#9743)
* updated minP to use early exit making use of sorted tokens
* ml/backend/ggml: allocate memory with malloc when loading model (#9822)
* runner: remove cache prompt flag from ollama runner (#9826)
We do not need to bypass the prompt caching in the ollama runner yet, as
only embedding models needed to bypass the prompt caching. When embedding
models are implemented they can skip initializing this cache completely.
* ollamarunner: Check for minBatch of context space when shifting
Models can specify that a group of inputs need to be handled a single
batch. However, context shifting didn't respect this and could trigger
a break anyways. In this case, we should instead trigger a context
shift earlier so that it occurs before the grouped batch.
Note that there still some corner cases:
- A long prompt that exceeds the context window can get truncated
in the middle of an image. With the current models, this will
result in the model not recognizing the image at all, which is
pretty much the expected result with truncation.
- The context window is set less than the minimum batch size. The
only solution to this is to refuse to load the model with these
settings. However, this can never occur with current models and
default settings.
Since users are unlikely to run into these scenarios, fixing them is
left as a follow up.
* Applied latest patches from McBane87
See this for details: https://github.com/whyvl/ollama-vulkan/issues/7#issuecomment-2708820861
Signed-off-by: Vadim Grinco <vadim@grinco.eu>
* Add ability to enable flash attention on vulkan (#4)
* discover: add flash attention handling for vulkan
* envconfig: fix typo in config.go
As part of the process some code was refactored and I added a new field
FlashAttention to GpuInfo since the previous solution didn't allow for a
granular check via vulkan extensions. As a side effect, this now allows
for granular per-device FA support checking in other places
---------
Signed-off-by: Vadim Grinco <vadim@grinco.eu>
Co-authored-by: zeo <108888572+zeozeozeo@users.noreply.github.com>
Co-authored-by: Louis Beaumont <louis.beaumont@gmail.com>
Co-authored-by: Daniel Hiltgen <dhiltgen@users.noreply.github.com>
Co-authored-by: Michael Yang <mxyng@pm.me>
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
Co-authored-by: Jesse Gross <jesse@ollama.com>
Co-authored-by: Nikita <50599445+nasrally@users.noreply.github.com>
This change bring in various interface cleanups along with greatly improving the performance of the sampler.
Tested with llama3.2 on local machine.
Improves performance from ~ 70 tokens/s -> 135 tokens/s with topK(40) enabled.
Without topK performance is ~ 110 tokens/s
Thomas Stocker
Vadim Grinco
Parth Sareen
Jeffrey Morgan