* added support for internvl's dynamic high-resolution (Qianfan-OCR needed)
* add min/max dynamic patch to gguf meta
* clean up
* simplified handling min/max dynamic patch
* reuse llava_uhd logic for slice images
* provide default values for older models
* flake8
* prevent writing 0 value to gguf
* remove duplicated resolution candidates with a better algorithm
* fix indentation
* format
* add protection from divide by zero
* change to 0 to be safe
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* misc : prefer ggml-org models in docs and examples
Prefer referring to known-good quantizations under ggml-org rather than
3rd-party uploaders.
* remove accidentally committed file
* server: (doc) clarify in-scope and out-scope features
* Apply suggestions from code review
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Two bugs in `server_models::load()` that affect router mode reliability:
**Bug 1: Deadlock when child process crashes**
When a child process is killed (e.g., SIGKILL from OS code signature
validation), the monitoring thread deadlocks on `stopping_thread.join()`
because the stopping_thread's wait predicate (`is_stopping`) is never
satisfied — the model name was never inserted into `stopping_models`.
`update_status()` is never reached and the model stays stuck in LOADING
state permanently.
Fix: extend the stopping_thread's wait predicate to also wake when the
child process is no longer alive (`!subprocess_alive()`). When woken by
a dead child, the thread skips the shutdown sequence and returns
immediately. The original `stopping_models.erase()` logic is preserved
for normal unloads.
**Bug 2: TOCTOU race bypasses `--models-max` (ref #20137)**
`unload_lru()` is called outside the mutex, then `load()` acquires the
lock afterward. Under concurrent requests, multiple threads observe
capacity and all proceed to load, exceeding the limit.
Fix: re-check capacity under the lock after `unload_lru()` returns.
If another thread filled the slot in the window between `unload_lru()`
and the lock acquisition, reject with an error instead of silently
exceeding the limit.
* tests : fix fetch_server_test_models.py
* server: to_json_oaicompat cached_tokens
Adds OpenAI and Anthropic compatible information about the
number of cached prompt tokens used in a response.
* webui: make server the source of truth for sampling defaults
* webui: fix Custom badge for sampling parameters
* webui: log user overrides after server sync
* chore: update webui build output
* fix: Default values for sampling settings config object
* chore: update webui build output
---------
Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com>
* add tests for model id parser
* add test case having activated params
* add structured tests for model id parser
* add ToDo
* feat: Improve model parsing logic + tests
* chore: update webui build output
---------
Co-authored-by: bluemoehre <bluemoehre@gmx.de>
* webui: fix model selector being locked to first loaded model
When multiple models are loaded, the auto-select effect would re-fire
on every loadedModelIds change, overriding the user's manual model
selection. Guard with selectedModelId so auto-select only kicks in
when no model is chosen yet.
* chore: update webui build output
* webui: use date in exported filename
Move conversation naming and export to utils
update index.html.gz
* webui: move literals to message export constants file
* webui: move export naming and download back to the conversation store
* chore: update webui build output
* webui: add comments to some constants
* chore: update webui build output
llama-perplexity -hf unsloth/Qwen3-0.6B-GGUF:Q4_K_M -f winogrande-debiased-eval.csv --winogrande
winogrande_score : tokenizing selected tasks
winogrande_score : calculating winogrande score over selected tasks.
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 46
failed to decode the batch, n_batch = 2048, ret = 1
winogrande_score: llama_decode() failed
same for hellaswag:
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 99
failed to decode the batch, n_batch = 2048, ret = 1
hellaswag_score: llama_decode() failed
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* llama : fix pooling assertion crash in chunked GDN detection path
The chunked fused Gated Delta Net detection in sched_reserve() calls
graph_reserve(16*n_seqs, n_seqs, n_outputs, ...) where n_outputs = n_seqs.
This creates a dimension mismatch in build_pooling() for embedding models
with mean/rank pooling: build_inp_mean() creates a tensor with shape
[n_tokens=16*n_seqs, ...] while t_embd is reduced to [n_outputs=n_seqs, ...]
via out_ids, causing ggml_mul_mat to assert on ggml_can_mul_mat(a, b).
Fix: pass n_tokens as n_outputs in the chunked GDN graph reservation,
matching the pattern used by the pp/tg worst-case reservations.
Regression introduced by #20340 (d28961d).
Same class of bug as #12517, fixed by #12545.
* server : add mean pooling tests to embedding test suite
Add test_embedding_pooling_mean and test_embedding_pooling_mean_multiple
to cover the --pooling mean codepath, which was previously untested.
These tests would have caught the regression introduced by #20340 where
build_pooling() crashes with a ggml_mul_mat assertion due to mismatched
dimensions in the chunked GDN detection path.
---------
Co-authored-by: Domenico Crupi <domenico@zerovolt.it>
* server: reset kill-switch on client error
This avoids triggering a server kill switch.
If the client sends a request that exceeds the configured context size, an appropriate HTTP 400 response is provided and no tokens are generated.
However since no tokens are generated, update_slots() increments n_empty_consecutive. If the client sends 3 such messages in a row, the server terminates.
* moved counter reset as per recommendation
* cont : minor
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit renames the the function `mtmd_get_audio_bitrate` to
`mtmd_get_audio_sample_rate` to better reflect its purpose.
The motivation for this is that the function currently returns the audio
sample rate, not the bitrate (sample_rate × bit_depth × channels), and
that is how it is used in the code as well.
This is a breaking change, but I believe mtmd is still in
experimental/development phase so it might be alright to simply rename.
* quantize : imatrix-fail early + code cleanup
* fix manual override printing
it's in the preliminary loop now, so needs to be on its own line
* revert header changes per ggerganov
* remove old #includes
* clarify naming
rename `tensor_quantization` to `tensor_typo_option` to descirbe its
functionality
* fix per barto
* Parse port numbers from MCP server URLs
* Pass scheme to http proxy for determining whether to use SSL
* Fix download on non-standard port and re-add port to logging
* add test
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* tests: add end-to-end tests per model architecture
* fixup for rebase
* fix use-after-free in llama-model-loader.cpp
* fix CI
* fix WebGPU
* fix CI
* disable CI for macOS-latest-cmake-arm64
* use expert_weights_scale only if != 0.0f
* comments
* Set C locale for consistent float formatting across all binaries.
* Add C locale setting to all tools binaries
Add std::setlocale(LC_NUMERIC, "C") to all 16 binaries in the tools/
directory to ensure consistent floating-point formatting.
* Apply suggestion from @JohannesGaessler
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* server : support multiple model aliases via comma-separated --alias
* server : update --alias description and regenerate docs
* server : multiple model aliases and tags
- address review feedback from ngxson
- --alias accepts comma-separated values (std::set, no duplicates)
- --tags for informational metadata (not used for routing)
- aliases resolve transparently in router via get_meta/has_model
- /v1/models exposes aliases and tags fields
* regenerate docs
* nits
* server : use first alias as model_name for backward compat
address review feedback from ngxson
* server : add single-model test for aliases and tags
* WIP: Add EuroBERT support with autoformatting changes
This commit includes:
- EuroBERT model implementation for GGUF conversion
- C++ backend support for EuroBERT architecture
- Unintended autoformatting changes to Python files
Saving before reverting formatting-only changes.
* feat: add back eos assert when not last token pooling
* feat: removed duplicated code and cleanup
* feat: removed not working architectures and unnecessary check
* fix: typo
* fix: dynamic pooling config
* feat: added an example model for eurobert
* feat: proper llama-vocab implementation for jina-v5
* fix: removed unnecessary comments
* server: fix query params lost when proxying requests in multi-model router mode
* server: re-encode query params using httplib::encode_query_component in proxy
* llama : remove write/read of output ids/logits/embeddings
This commit removes the write/read of output ids, logits and
embeddings from the llama context state.
Refs: https://github.com/ggml-org/llama.cpp/pull/18862#issuecomment-3756330941
* completion : add replying of session state
This commit updates the session handing in the completion tool to handle
the that logits are no longer stored in the session file. Instead, we
need to replay the last token to get the logits for sampling.
* common : add common_prompt_batch_decode function
This commit adds a new function which is responsible for decoding prompt
and optionally handle the saving for session data.
* update save-state.cpp to use llama_state_load_file
This commit updates the save-load-state example to utilize the new
llama_state_load_file function for loading the model state from a file.
And it also replays the last token after loading since this state is now
stored before the last token is processed.
* examples : set n_seq_max = 2 for ctx3
This commit updates the save-load-state example to set the n_seq_max
parameter to 2 when initializing the ctx3 context.
The motivation for this change is that using 1 as n_parallel/n_seq_max
the context only supports one sequence, but the test laster tries to
use a second sequence which results in the following error:
```console
main : loaded state with 4 tokens
main : seq 0 copied, 225760 bytes
main : kv cache cleared
find_slot: seq_id=1 >= n_seq_max=1 Try using a bigger --parallel value
state_read_meta: failed to find available cells in kv cache
```
This seems to only happen for recurrent/hybrid models.
Xuan-Son Nguyen
Aleksander Grygier
Pascal
bssrdf
DorianRudolph
Evgeny Kurnevsky
ddh0
Sigbjørn Skjæret
Piotr Wilkin (ilintar)
Georgi Gerganov
Ben Racicot
Tomeamis
Ryan Goulden
crsawyer
Julien Chaumond
Woof Dog
Chedrian07
Adrien Gallouët
ZeroV0LT
SoftwareRenderer
Daniel Bevenius
DAN™
Evan Huus
Aaron Teo
Johannes Gäßler
decahedron1
Tom Vaucourt
Roj234
Marcel Petrick
SamareshSingh
standby24x7
Sami Kama
drrros
Maximilian Werk
yggdrasil75
Radoslav Gerganov
Kilian Krampf
Aldehir Rojas