v4.3
Changes ik_llama.cpp support : Add ik_llama.cpp as a new backend: new textgen-portable-ik portable builds, new --ik flag for full installs. ik_llama.cpp is a fork by the author of the imatrix quants, including support for new quant types, significantly more accurate KV cache quantization (via Hadamard KV cache rotation, enabled by default), and optimizations for MoE models and CPU inference. API: Add echo + logprobs for /v1/completions . The completions endpoint now supports the echo and logprobs parameters, returning token-level log probabilities for both prompt and generated tokens. Token IDs are also included in the output via a new top_logprobs_ids field. Further optimize my custom gradio fork, saving up to 50 ms per UI event (button click, etc). Transformers: Autodetect torch_dtype fr
Provide feedback
Saved searches
Use saved searches to filter your results more quickly
Sign up
Appearance settings
text-gen-webui Releases
https://github.com/oobabooga/text-generation-webui/releases/tag/v4.3Sign in to highlight and annotate this article

Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
llamamodeltransformertrunk/834da621b18df19b513ee787c6926d43f928adfc: add API to check if a tensor is symm-mem-tensor (#178947)
In Helion autotuner, we need clone a input symm memory tensor properly if the kernel inplace update it. That requires us to know if a tensor is a symm memory tensor. Right now I call rendezvous for the tensor. If no exception is thrown, then it's a symm memory tensor. But it's not ideal there will be a lot of warnings complaining calling rendezvous on non-symm memory tensor I'll need to pass in the process group name to this API. But fundamentally check if a tensor is a symmetric memory tensor does not require the process group name. Pull Request resolved: #178947 Approved by: https://github.com/ngimel , https://github.com/fegin
trunk/34b6e17d1a24014822e71d2f0726adafc230ed0b: [Native DSLs] DSL Registry, base tests rework (#178381)
Summary: Note: Due to git-related shenanigans, this has subsumed #178518 Tests cleaning based on more explicit instructions to claude - should be better aligned with other torch tests. Add a separate registry for DSLs (alongside the existing registry for overrides). This allows a) a centralized place to query the availability of different DSLs, and b) a cleaner way to test / test for multiple DSLs without requiring manually adding each new DSL. Add Test skip decorators for current DSL list Test Plan: pytest -sv test/python_native/ Signed-off-by: Simon Layton [email protected] Pull Request resolved: #178381 Approved by: https://github.com/drisspg , https://github.com/albanD ghstack dependencies: #178637
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Open Source AI

From SWE-ZERO to SWE-HERO: Execution-free to Execution-based Fine-tuning for Software Engineering Agents
arXiv:2604.01496v1 Announce Type: new Abstract: We introduce SWE-ZERO to SWE-HERO, a two-stage SFT recipe that achieves state-of-the-art results on SWE-bench by distilling open-weight frontier LLMs. Our pipeline replaces resource-heavy dependencies with an evolutionary refinement strategy: (1) SWE-ZERO utilizes large-scale, execution-free trajectories to master code semantics and repository-level reasoning, and (2) SWE-HERO applies targeted, execution-backed refinement to transition these semantic intuitions into rigorous engineering workflows. Our empirical results set a new benchmark for open-source models of comparable size. We release a dataset of 300k SWE-ZERO and 13k SWE-HERO trajectories distilled from Qwen3-Coder-480B, alongside a suite of agents based on the Qwen2.5-Coder series.

A Quick Note on Gemma 4 Image Settings in Llama.cpp
In my last post, I mentioned using --image-min-tokens to increase the quality of image responses from Qwen3.5 . I went to load Gemma 4 the same way, and hit an error: [58175] srv process_chun: processing image... [58175] encoding image slice... [58175] image slice encoded in 7490 ms [58175] decoding image batch 1/2, n_tokens_batch = 2048 [58175] /Users/socg/llama.cpp-b8639/src/llama-context.cpp:1597: GGML_ASSERT((cparams.causal_attn || cparams.n_ubatch > = n_tokens_all ) "non-causal attention requires n_ubatch >= n_tokens" ) failed [58175] WARNING: Using native backtrace. Set GGML_BACKTRACE_LLDB for more info. [58175] WARNING: GGML_BACKTRACE_LLDB may cause native MacOS Terminal.app to crash. [58175] See: https://github.com/ggml-org/llama.cpp/pull/17869 [58175] 0 libggml-base.0.9.11.dylib 0


Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!