* model-conversion : add device option to run-org-model.py
This commit refactors the `run-org-model.py` script to include a
`--device` argument, to allow users to specify the device on which to
run the model (e.g., cpu, cuda, mps, auto).
It also extracts a few common functions to prepare for future changes
where some code duplication will be removed which there currently
exists in embedding scripts.
The Makefile is also been updated to pass the device argument, for
example:
```console
(venv) $ make causal-verify-logits DEVICE=cpu
```
* fix error handling and remove parser reference
This commit fixes the error handling which previously referenced an
undefined 'parser' variable.
This commit adds the trust_remote_code=True parameter when loading
models and configurations in the embedding model conversion scripts.
It also adds a cast to float for models that might use a data type that
is not supported by python, for example bfloat16.
The motivation for this is that some models may require custom code to
be executed during loading, and setting trust_remote_code to True avoids
getting prompted for confirmation.
Future work will consolidate the embedding conversion scripts with the
causal conversion scripts to avoid code duplication. But in the mean
time it would be nice to have this fix in place.
This commit adds a --verbose flag to the run-org-model.py script to
enable or disable detailed debug output, such as input and output
tensors for each layer. Debug utilities (summarize, debug_hook,
setup_rope_debug) have been moved to utils/common.py.
The motivation for this is that the detailed debug output can be useful
for diagnosing issues with model conversion or execution, but it can
also produce a large amount of output that may not always be needed.
The script will also be further cleaned/refactored in follow-up commits.
* UI: implement basic UI components
* util: implement performance monitor; wrap it with a viewmodel
* util: implement user preferences utility
* UI: implement core flow's screens
* UI: add a new MainActivity; update manifest
* [WIP] DI: implement simple local vm factory provider
* UI: disable triggering drawer via gesture; enable alert dialog on back navigation inside conversation and benchmark
* UI: allow drawer's gesture control only on Home and Settings screens; enable alert dialog on back navigation inside conversation and benchmark
* UI: split a nested parent settings screen into separate child settings screens
* UI: polish system prompt setup UI
* Deps: bump Kotlin plugin; introduce KSP; apply in :app subproject
* DB: setup Room database
* data: introduce repo for System Prompt; flow data from Room to VM
* bugfix: properly handle user's quitting conversation screen while tokens in generation
* UI: rename `ModeSelection` to `ModelLoading` for better clarity
* UI: update app name to be more Arm
* UI: polish conversation screen
* data: code polish
* UI: code polish
* bugfix: handle user quitting on model loading
* UI: locks user in alert dialog when model is unloading
* vm: replace token metrics stubs with actual implementation
* UI: refactor top app bars
* nit: combine temperatureMetrics and useFahrenheit
* DI: introduce Hilt plugin + processor + lib dependencies
* DI: make app Hilt injectable
* DI: make viewmodels Hilt injectable
* DI: replace manual DI with Hilt DI
* UI: optimize AppContent's composing
* bugfix: wait for model to load before navigating to benchmark screen; use NavigationActions instead of raw navController
* UI: navigation with more natural animated transitions
* DI: Optimize AppModule
* Feature: Introduce ModelRepository and ModelsManagementViewModel; update AppModule
* UI: polish UI for ModelsManagementScreen; inject ModelsManagementVieModel
* DI: abstract the protocol of SystemPromptRepository; update AppModule
* data: [WIP] prepare for ModelRepository refactor & impl
* data: introduce Model entity and DAO; update DI module
* UI: replace Models Management screen's stubbing with instrumentation
* UI: polish sort order menu
* data: import local model with file picker
* bugfix: use List instead of Collection for ModelDao's deletion
* data: add a util file for extracting file name & size and model metadata
* UI: enrich ModelManagementState; extract filename to show correct importing UI
* UI: implement multiple models deletion; update Models Management screen
* UI: handle back navigation when user is in multi-selection mode
* util: extract file size formatting into ModelUtils
* UI: add a confirmation step when user picks a file; refactor model import overlay into AlertDialog
* UI: extract a shared ModelCard component
* UI: replace model selection screen's data stubbing; add empty view
* nit: tidy SystemPromptViewModel
* Util: split FileUtils from ModelUtils; extract copy methods into FileUtils
* data: pass through getModelById from ModelDao into ModelRepository
* core: extract conversation and benchmark logics into InferenceManager; add logs and missing state updates in stub InferenceEngine
* vm: split mono MainViewModel into separate individual ViewModels
* vm: merge SystemPromptViewModel into ModelLoadingViewModel
* core: break down InferenceManager due to Interface Segregation Principle
* UI: show model card in Model Loading screen
* UI: show model card in Conversation screen
* UI: unify Model Card components
* core: swap in LLamaAndroid and mark stub engine for testing only
* data: allow canceling the ongoing model import
* UI: update UI ongoing model import's cancellation
* LLama: update engine state after handling the cancellation of sendUserPrompt
* VM: handle the cancellation of ongoing token generation
* LLama: refactor loadModel by splitting the system prompt setting into a separate method
* feature: check for available space before copying local model
* UI: centralize the AppScaffold and modularize its configs
* UI: refactor BottomBarConfig.ModelsManagement APIs
* UI: combine TopBarConfig and BottomBarConfig into each route's ScaffoldConfig
* UI: replace ugly optional as casts in AppScaffold with extension functions
* UI: fix the typo `totalGb` in `StorageMetrics`
* UI: remove code duplication in sort menu
* LLama: add ModelUnloadingState to engine State; add missing state checks in stub engine; fix instrumentation engine's error messages
* UI: refactor back handling by removing centralized BackHandlerSetup and UnloadModelConfirmationDialog from AppContent
* UI: implement BenchmarkScreen's individual back handling
* LLama: add a new Initializing state; ; add two extension properties; rename LibraryLoaded state to Initialized
* UI: Introduce an abstract ViewModel to handle additional model unloading logics
* UI: expose a single facade ModelUnloadDialogHandler; move UnloadModelState into ModelUnloadingViewModel.kt
* UI: migrate ModelLoadingScreen onto ModelLoadingViewModel; update & refine ModelLoadingScreen
* UI: migrate ConversationViewModel onto ModelLoadingViewModel; update & refine ConversationScreen
* nit: extract app name into a constant value; remove unused onBackPressed callbacks
* UI: update AppContent to pass in correct navigation callbacks
* nit: polish ModelLoadingScreen UI
* core: throw Exception instead of returning null if model fails to load
* navigation: sink model loading state management from AppContent down into ModelLoadingScreen; pass ModelLoadingMetrics to Benchmark and Conversation screens
* gguf: add GGUF metadata data holder and its corresponding extractor implementation
* DB: introduce Kotlin serialization extension's library and plugin; add Room runtime library
* GGUF: make GgufMetadata serializable in order to be compatible with Room
* nit: refactor data.local package structure
* nit: rename lastUsed field to dateLastUsed; add dateAdded field
* UI: refactor ModelCard UI to show GGUF metadata
* UI: update ModelSelectionScreen with a preselect mechanism
* UI: polish model card
* nit: allow deselect model on Model Selection screen
* nit: revert accidental committing of debug code
* UI: polish ModelLoading screen
* util: extract formatting helper functions from FileUtils into a new FormatUtils
* UI: polish model cards on Benchmark and Conversation screens to show model loading metrics
* UI: show a Snack bar to warn user that system prompt is not always supported
* UI: handle back press on Model Selection screen
* UI: finally support theme modes; remove hardcoded color schemes, default to dynamic color scheme implementation
* feature: support searching on Model Selection screen
* nit: move scaffold related UI components into a separate package
* UI: extract InfoView out into a separate file for reusability
* data: move Model related actions (query, filter, sort) into ModelInfo file
* UI: animate FAB on model preselection states
* feature: support filtering in Model Management screen
* ui: show empty models info in Model Management screen
* ui: add filter off icon to "Clear filters" menu item
* [WIP] ui: polish Benchmark screen; implement its bottom app bar
* ui: polish Benchmark screen; implement its bottom app bar's rerun and share
* nit: disable mode selection's radio buttons when loading model
* feature: implement Conversation screen's bottom app bar
* pkg: restructure BottomAppBars into separate files in a child package
* pkg: restructure TopBarApps into separate files in a child package
* pkg: restructure system metrics into a separate file
* UI: polish Conversation screen
* data: update system prompt presets
* UI: allow hide or show model card on Conversation & Benchmark screens; fix message arrangement
* data: update & enhance system prompt presets
* deps: introduce Retrofit2
* data: implement HuggingFace data model, data source with Retrofit API
* data: update Model data repository to support fetching HuggingFace models
* [WIP] UI: replace the HuggingFace stub in Model Management screen with actual API call
* UI: map language codes into country Emojis
* ui: add "clear results" action to Benchmark screen
* nit: print current pp & tg in llama-bench
* UI: disable landscape mode; prevent duplicated benchmark running
* llama: migrate C/CXX flags into CMakeList
* [WIP] llama: ABI split builds five .so artifacts.
However, all .so are performing on SVE level
* [WIP] llama: ABI split where five tiers are built sequentially.
* [WIP] llama: disable OpenMP in ABI split since most SoCs are big.LITTLE
* [WIP] llama: enable KleidiAI and disable tier 4 due to `+sve+sve2` bug caused by `ggml_add_cpu_backend_variant_impl` as explained below
```CMake
if (NOT SME_ENABLED MATCHES -1)
...
set(PRIVATE_ARCH_FLAGS "-fno-tree-vectorize;${PRIVATE_ARCH_FLAGS}+sve+sve2")
...
```
* core: add Google's cpu_features as a submodule
* core: implement cpu_detector native lib
* core: swap out hardcoded LlamaAndroid library loading
* core: add back OpenMP due to huge perf loss on TG128
* misc: reorg the pkg structure
* misc: rename LlamaAndroid related class to InferenceEngine prefixes
* [WIP] lib: move GgufMetadata into the lib submodule
* lib: expose GgufMetadataReader as interface only
* lib: replace the naive & plain SharedPreferences with DataStore implementation
* lib: hide the internal implementations, only expose a facade and interfaces
* lib: expose Arm features
* di: add a stub TierDetection; provide both actual impl and stub in AppModule
* UI: add visualizer UI for Arm features
* misc: UI polish
* lib: refactored InferenceEngineLoader; added a `NONE` Llama Tier
* UI: support `NONE` Llama Tier in general settings
* lib: optimize engine loader; always perform a fresh detection when cache is null
* remote: add HuggingFaceModelDetails data class
* remote: refine HuggingFaceModel data class
* nit: remove `trendingScore` field from HuggingFace model entities, weird...
* remote: refactor HuggingFaceApiService; implement download feature in HuggingFaceRemoteDataSource
* remote: fix the incorrect parse of HuggingFace's inconsistent & weird JSON response
* UI: scaffold Models Management screen and view model
* UI: implement a dialog UI to show fetched HuggingFace models.
* UI: use a broadcast receiver to listen for download complete events and show local import dialog.
* data: handle network exceptions elegantly
* pkg: restructure `data`'s packages
* data: extract local file info, copy and cleanup logics into LocalFileDataSource
* nit: minor UI patch; add missing comments
* bugfix: tapping "Home" in navigation drawer should simply close it without any navigation action.
* UI: improve autoscroll during token generation
* lib: tested on JFrog Artifactory for Maven publishing
* UI: show RAM warning if model too large
* UI: polish model management screen's error dialog
* util: add more items into the mapping table of ISO 639-1 language code to ISO 3166-1 country code
* llm: properly propagate error to UI upon failing to load selected model
* UI: avoid duplicated calculation of token metrics
* lib: read & validate the magic number from the picked source file before executing the import
* UI: add "Learn More" hyperlinks to Error dialog upon model import failures
* lib: refactor the GgufMetadataReader to take InputStream instead of absolute path as argument
* lib: fix the `SIMD` typo in Tier description
* core: verify model file path is readable
* lib: add UnsupportedArchitectureException for triaged error message
* util: split FormatUtils into multiple utils for better readability
* UI: change benchmark screen from raw markdown to table view
* bugfix: reset preselection upon running the preselected model
* misc: linter issue
* bugfix: fix the malfunctioning monitoring switch
* UI: update Arm features indicator; fix the broken hyperlinks
* UI: add quick action buttons to benchmark screen's result card
* UI: hide share fab after clearing all benchmark results
* UI: fix the model unload dialog message; elevate the model card and hide it by default on Conversation screen;
* UI: hide the stubbing actions in Conversation screen
* UI: add show/hide stats control to conversation screen's assistant message bubble; fix placeholder
* UI: add a info button to explain token metrics
* misc: remove the redundant `Companion` added due to refactoring
* UI: show corresponding system metrics detailed info upon tapping RAM / storage / temperature indicator
* UI: add info button to System Prompt switch; expand the model card by default
* UI: disable tag & language chips; add section headers to explain what they are
* misc: replace top bar indicator's spacer with padding
* UI: merge the Model Selection and Model Management into a unified Models screen
* UI: split the ModelsManagementViewModel from a unified ModelsViewModel due to huge complexity
* UI: add model loading in progress view; polish the empty model info view
* UI: polish the bottom bars and info view when no models found; show loading in progress while fetching models
* build: [BREAKING] bump the versions of libraries and plugins
* UI: fix the breaking build
* UI: add Tooltip on Import FAB for user onboarding
* UI: adds AppPreferences to track user onboarding status
* UI: tracks user's first success on importing a model
* data: add hand crafted rules to filter the models fetched from HuggingFace API
* UI: update app name & about; polish top bars' indicators & buttons
* UI: polish Hugging Face download dialog UI
* UX: implement onboarding tooltips for model import and onboarding
* misc: use sentence case for CTA button labels
* [WIP] UI: add Arm color palette from Philip.Watson3
* UI: address Rojin's UX feedbacks
* UI: address Rojin's UX feedbacks - part 2
* UI: update Arm color palette from Philip.Watson3
* data: make sure fetch preselected models in the same order of their IDs
* UI: fix UI issues in the generic settings screen and navigation drawer
* nit: address Rojin's feedbacks on model import message again
* nit: append `®` to all `Arm` labels
* UI: extract a reusable InfoAlertDialog
* core: support GGML_CPU_ALL_VARIANTS on Android!
* core: restructure Kleidi-Llama library
* core: organizing cmake arguments
* data: sort preselected models according to device's available RAM
* app: update adaptive + themed + legacy icons and app name
* UI: fix the font size auto scaling for ArmFeaturesVisualizer
* core: further improve the performance on native methods
* UI: minor color palette changes; emphasize the bottom bar FABs; fix Settings Screen menu item label
* UI: make more room for assistant message bubble's width
* UI: better usage of tertiary colors to highlight model cards but not for warnings
* UI: fix the layout issue on large font sizes
* lib: support x86-64 by dynamically set Arm related definitions
* lib: replace the factory pattern for deprecated tiered lib loading with single instance pattern
* llama: update the library name in JNI and CMake project
* llama: update the library's package name and namespace
* llama: update the app's package name and namespace
* app: bump ksp version
* app: remove deprecated SystemUIController from accompanist by migrating to EdgeToEdge
* app: extract AppContent from MainActivity to a separate file in ui package
* lib: add File version for GGUF Magic number verification
* lib: perform engine state check inclusively instead of exclusively
* lib: change `LlamaTier` to `ArmCpuTier`
* lib: remove kleidi-llama related namings
* cleanup: remove Arm AI Chat/Playground app source code; replace with the basic sample app from https://github.com/hanyin-arm/Arm-AI-Chat-Sample
Note: the full Google Play version of AI Chat app will be open will be open sourced in another repo soon, therefore didn't go through the trouble of pruning the history using `git filter-repo` here.
* [WIP] doc: update main and Android README docs; add self to code owners
* lib: revert System.load back to System.loadLibrary
* jni: introduce a logging util to filter different logging levels on different build types
* lib: enable app optimization
* doc: replace stub Google Play app URL with the actual link add screenshots; add my GitHub ID to maintainer list
* Remove cpu_features
* Fix linters issues in editorconfig-checker job
https://github.com/ggml-org/llama.cpp/actions/runs/19548770247/job/55974800633?pr=17413
* Remove unnecessary Android CMake flag
* purge include/cpu_features directory
---------
Co-authored-by: Han Yin <han.yin@arm.com>
This commit adds a note to the README in the model-conversion
examples, advising developers to verify that previous versions of models
pass logits verification before adding new models from the same family.
This commit updates the embedding model verification script to use the
CONVERTED_EMBEDDING_MODEL environment variable instead of using the
EMBEDDING_MODEL_PATH (the original embedding model path) as the basis
for the converted model file name.
The motivation for this that currently if the converted embedding model
file name differs from the original embedding model directory/name the
verification script will look for the wrong .bin files that were
generating when running the models.
* model-conversion : use CONVERTED_MODEL value for converted model [no ci]
This commit updates the model verification scripts to use the
CONVERTED_MODEL environment variable instead of using the MODEL_PATH
(the original model path) as the basis for the converted model file
name.
The motivation for this that currently if the converted model file name
differs from the original model directory/name the verification scripts
will look for the wrong .bin files that were generating when running the
models.
For example, the following steps were not possible:
```console
(venv) $ huggingface-cli download google/gemma-3-270m-it --local-dir ggml-org/gemma-3-270m
(venv) $ python3 convert_hf_to_gguf.py ggml-org/gemma-3-270m --outfile test-bf16.gguf --outtype bf16
(venv) $ cd examples/model-conversion/
(venv) $ export MODEL_PATH=../../ggml-org/gemma-3-270m
(venv) $ export CONVERTED_MODEL=../../test-bf16.gguf
(venv) $ make causal-verify-logits
...
Data saved to data/llamacpp-test-bf16.bin
Data saved to data/llamacpp-test-bf16.txt
Error: llama.cpp logits file not found: data/llamacpp-gemma-3-270m.bin
Please run scripts/run-converted-model.sh first to generate this file.
make: *** [Makefile:62: causal-verify-logits] Error 1
```
With the changes in this commit, the above steps will now work as
expected.
This commit removes the maximum difference check from the
compare-logits.py which would stop early if the difference between
the logits exceeded a threshold.
The motivation for removing this is that it can be useful to be able to
get the complete log for debugging/reporting purposes.
This commit adds the token ids to the printed prompt outputs.
The motivation for this is that is can be useful to see the actual token
ids alongside the token strings for debugging.
* ggml : add GGML_SCHED_NO_REALLOC option to disable reallocations in ggml_backend_sched
Enabled in ggml-ci for testing.
* llama : update worst-case graph for unified cache
* ci : disable op offload in some tests
* fix spelling
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Qwen3 Next - cleaned up version
* Whitespaces and stuff
* Correct minor errors
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Misc. fixes.
* Clean up code, add missing hybrid qualifier
* Did someone transpose the SOLVE_TRI result matrix? Perhaps...
* Whitespace
* Proper tensors for cb calls
* Use llama-graph.h vertical alignment
* BROKEN: chunking
* Set new tensors as inputs.
* Proper chunk logic
* It's the circle of life...
* More shenanigans for n_seq > 1
* Nail in the coffin?
* Fix Windows build
* Eh, one fails on Windows, the other fails on Mac... just use general capture.
* quant : cleanup
* model : cleanup
* qwen3 : cleanup
* cont : cleanup
* cont : cleanup
* ggml : revert change
* qwen3 : cleanup
* cont : cleanup
* Readd cmath
* qwen3 : fix typo
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Usual suspects
* fix my bad suggestion
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit removes the `--backend-dist` option and instead uses the
configured --samplers chain to determine which samplers run on the
backend.
Backend sampling is still enabled using With `--backend_sampling`, and
the sampler chain, either explictly specified using `--samplers` or the
default, is automatically analyzed to determine which samplers can run
on the backend. The system finds the longest contiguous chain of
backend supported samplers from the start of the sampler sequence.
For example:
* If the chain is `top-k -> temperature -> top-p`, and both `top-k` and
`temperature` are backend-supported but `top-p` is not, then `top-k`
and `temperature` will run on the backend, while `top-p` and
subsequent samplers run on the CPU.
* If all configured samplers are supported, the final distribution
sampling will also happen on the backend, transferring only the
sampled token IDs back to the host.
* If the sampler chain starts with an unsupported sampler (e.g.,
`penalties`), all sampling runs on the CPU. Note that this is
currently the case with the default sampler so to use backend sampling
it is required to specify a sampler chain. See below for an example.
The following shows how llama-cli can be run with backend sampling:
```console
$ llama-cli -m models/Qwen2.5-VL-3B-Instruct-Q8_0.gguf \
--prompt 'What is the capital of Sweden?' \
-n 20 \
-no-cnv \
--verbose-prompt \
-ngl 40 \
--backend-sampling \
--samplers 'top_k;temperature'
```
In this case the all sampling will happen on the backend since both
`top_k` and `temperature` are supported backend samplers.
To enable a partial backend sampling (hybrid sampling), for example
running `top_k` and `temperature` on the backend and `typ_p` on the CPU
the following sampler chain could be specified:
```console
$ llama-cli -m models/Qwen2.5-VL-3B-Instruct-Q8_0.gguf \
--prompt 'What is the capital of Sweden?' \
-n 20 \
-no-cnv \
--verbose-prompt \
-ngl 40 \
--backend-sampling \
--samplers 'top_k;temperature;top_p'
```
If this looks good then I'll follow up with updates the llama-cli and
llama-server documentation to reflect these changes.
This commit adds the --kv-unified flag to the usage example
in the README.md file for the batched example.
The motivation for this is that without this flag the example will fail
with the following error:
```console
Hello my name is
split_equal: sequential split is not supported when there are coupled
sequences in the input batch (you may need to use the -kvu flag)
decode: failed to find a memory slot for batch of size 4
main: llama_decode() failed
```
Georgi Gerganov
Daniel Bevenius
Neo Zhang
Xuan-Son Nguyen
Naco Siren
Piotr Wilkin (ilintar)
Oliver Simons
Igor Smirnov
Diego Devesa
william pan