On the llama engine, when we compute the memory layout, we reserve
a buffer to allow for some flexibility for incorrect estimates.
This is subtracted from GPU free memory and on GPUs with limited
memory, it may underflow.
Fixes#13494
* Revert "add support for NVIDIA Nemotron 3 Nano"
This reverts commit e7d2ae9d69.
* GGML update to 380b4c984
Remove MaskBatchPadding as GGML_KQ_MASK_PAD is no longer present (no
padding required)
* update to c45f89d55
* ec98e2002
solar pro needed more adjusting - needs verification
* review comments
Refactored the ConfigV2 and RootFS types from server/images.go to a new types/model/config.go file under the model package. Updated all references to use model.ConfigV2 and model.RootFS. This allows for use in other projects without worrying about compiling the c code in the llama package.
The ggml/src/CMakeLists.txt uses GGML_VERSION_MAJOR for the shared
library SOVERSION property, but these variables were not defined when
building from ollama's CMakeLists.txt.
This caused libggml-base.so to be named with a literal "SOVERSION"
suffix (libggml-base.so.SOVERSION) instead of the actual version
number (libggml-base.so.0).
The fix adds the required GGML_VERSION_* variables before including
the ggml subdirectory.
Fixes#13436
* flash attn: add auto mode for llama engine
If the user does not specify fa in the environment, use auto-mode.
* review comments
* ensure kv cache quantized types have FA explicitly enabled
additional review comments
This changes the default behavior to use the Ollama engine for supported
models, while retaining the ability to disable the Ollama engine and
fall back to the Llama engine. Models in the OllamaEngineRequired list
will always run on the Ollama engine.
* docs: add docs for v1/responses and rework openai compat section
I reworked the examples to be separated by topic and to be fully
runnable (i.e., they now log output instead of just suggesting how a
call might be made).
We now use `<CodeGroup>`s so that each example has a dropdown on the
docs site for users to choose, which makes the examples a lot more
digestible (since you only see approx 1/3 of the code you used to).
I also added a new tool to extract code examples into files so that it's
easier to actually run them and check that they work.
## Example
```shell
go run docs/tools/extract-examples/main.go docs/api/openai-compatibility.mdx
```
Output:
```
Extracting code examples to: /var/folders/vq/wfm2g6k917d3ldzpjdxc8ph00000gn/T/mdx-examples-3271754368
- 01_basic.py
- 01_basic.js
- 01_basic.sh
- 02_responses.py
- 02_responses.js
- 02_responses.sh
- 03_vision.py
- 03_vision.js
- 03_vision.sh
Extracted 9 file(s) to /var/folders/vq/wfm2g6k917d3ldzpjdxc8ph00000gn/T/mdx-examples-3271754368
To run examples:
cd /var/folders/vq/wfm2g6k917d3ldzpjdxc8ph00000gn/T/mdx-examples-3271754368
npm install # for JS examples
then run individual files with `node file.js`, `python file.py`, `bash file.sh`
```
In the future we should consider actually running the examples in CI and
having some sort of acceptance test so we can automatically detect when
our examples break. So this is just a start in that direction.
* Update docs/api/openai-compatibility.mdx
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>
* Update docs/api/openai-compatibility.mdx
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>
---------
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>
This PR detects embedding models and sets batch_size = context_size so the full input fits in a single batch.
Previously, if batch size was smaller than the input, tokens could be split across batches and cause a SIGTRAP crash.
This change ensures all tokens stay in one batch and prevents crashes.
Fixes: #12938#13054
Co-authored-by: Jesse Gross <jesse@ollama.com>
* feat: Bump llama.cpp to the latest master (17f7f4b)
This brings in significant improvements to prefill performance for all
models using the SSM_CONV and SSM_SCAN ops (granite4, jamba, falcon-h,
nemotron-h, Qwen3 Next) on Apple Metal.
See https://github.com/ggml-org/llama.cpp/pull/17876
Branch: LlamaCPPMetalSSMImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Update patches 1-4
Branch: LlamaCPPMetalSSMImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Update patches 5-12
Branch: LlamaCPPMetalSSMImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Update patches 13-18
Branch: LlamaCPPMetalSSMImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Update patch 20
Branch: LlamaCPPMetalSSMImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Update patches 21-31
Branch: LlamaCPPMetalSSMImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Sync vendored code
The two files I'm not sure about here are the swap from gemma3-iswa.cpp to
gemma3.cpp (I chose to include this because I think it's required), and the
inclusion of `ggml-zendnn.h` which I chose to omit.
Branch: LlamaCPPMetalSSMImprovements
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
---------
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
