Weekly GitHub Report for Llama.cpp - 2025-01-13 12:00:34
Weekly GitHub Report for Llama.cpp
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Table of Contents
I. News
1.1 Recent Version Releases:
The current version of this repository is b4458
1.2 Version Information:
The version released on January 10, 2025, introduces key updates and changes, though specific details are not provided in the given data. Notable highlights or trends cannot be identified without additional information.
II. Issues
2.1 Top 5 Active Issues:
We consider active issues to be issues that that have been commented on most frequently within the last week. Bot comments are omitted.
-
Vulkan related question: what's the different between server and cli? : This issue involves a user experiencing core dumps when running llama-server and stable-diffusion.cpp on Vulkan in Termux, while llama-cli functions correctly, and the user suspects the absence of glslangvalidator during the build process might be related. The user seeks assistance in understanding the differences between server and client operations in this context and is looking for potential solutions to the problem.
- The comments discuss potential causes for the core dumps, including missing dependencies and differences in how server and client processes interact with the GPU. Suggestions include checking for GPU/driver compatibility, considering OpenCL as an alternative, and exploring Android-specific process management. The user shares additional logs and attempts to resolve the issue by removing certain packages and using OpenBLAS, but challenges persist.
- Number of comments this week: 9
-
Eval bug: Qwen2-VL Hallucinates image content on Vulkan backend: This issue reports a bug in the Qwen2-VL model when using the Vulkan backend, where the model generates descriptions unrelated to the provided image, despite working correctly on the CPU backend. The user notes that while the Vulkan backend is not officially supported for Qwen2-VL, it should only result in slower performance rather than incorrect outputs.
- The comments discuss various troubleshooting steps, including testing with an F16 vision projector and enabling GGML_VULKAN_CHECK_RESULTS to identify broken operations. Users encounter issues with linker errors and unresolved externals, suggesting adding CPU backend source files to ggml-vulkan. Despite some users reporting it works on certain setups, others confirm the issue persists, particularly when running CLIP on Vulkan, leading to a consensus to keep the issue open until resolved.
- Number of comments this week: 7
-
Misc. bug: SYCL out of memory error: This issue reports a memory allocation error encountered when using the SYCL backend in a llama.cpp project, which does not occur with the VULKAN backend under similar conditions. The user describes that the error arises when attempting to allocate 568 MB of memory on a system with 16 GB of shared GPU memory, suggesting a potential inefficiency in the SYCL backend's memory management.
- The comments discuss potential solutions and optimizations, including reducing context length and using the
-nkvooption, which works but is slower. There is speculation about memory inefficiency in the SYCL backend, with plans for future optimizations. The discussion also touches on the possibility of a memory allocation limitation similar to OpenCL's, but the issue is identified as excessive memory usage during batched matrix multiplication. Suggestions include testing with--no-warmupand a smaller batch size. - Number of comments this week: 7
- The comments discuss potential solutions and optimizations, including reducing context length and using the
-
DeepSeek Models (V2/V3) Hang with ROCm Backend: This issue involves a problem with running DeepSeek models (V2 and V3) using the ROCm backend, where the models load into VRAM but fail to generate any output, resulting in one GPU being stuck at 100% utilization while the others remain idle. The problem persists across multiple attempts and is consistent with different quantization methods, although the models run as expected when using CPU-only.
- The comments discuss attempts to diagnose the issue, including running commands to test CPU-only performance, which works as expected, and observing that the problem occurs after a fresh reboot. One user notes that the issue resolves temporarily after running a specific command or reverting to an older commit, but reappears after rebooting. Another user suggests letting the process run longer, but the original poster reports no change after 30 minutes, with one GPU still at 100% utilization and no output generated.
- Number of comments this week: 7
-
Again, the releases don't have the libraries.: This issue is about a recurring problem where the releases of the project do not include necessary shared libraries, specifically resulting in an error related to the missing
libllama.sofile. The problem has been noted in previous versions, and users are experiencing difficulties in building and running the application due to this missing library.- Users discuss testing binaries on different platforms, noting that some versions work while others do not. A script is shared to identify working versions, and suggestions are made to adjust library paths or compile statically. The issue is confirmed on multiple platforms, and detailed logs are provided to help diagnose the problem.
- Number of comments this week: 6
2.2 Top 5 Stale Issues:
We consider stale issues to be issues that has had no activity within the last 30 days. The team should work together to get these issues resolved and closed as soon as possible.
As of our latest update, there are no stale issues for the project this week.
2.3 Open Issues
This section lists, groups, and then summarizes issues that were created within the last week in the repository.
Issues Opened This Week: 30
Summarized Issues:
- Missing Shared Libraries: Users have reported issues with missing shared libraries, such as
libllama.so, which cause execution errors in the llama.cpp project. Various troubleshooting steps, including adjusting library paths and compiling statically, have been suggested to resolve these issues.
- Compilation Errors: Several issues have been reported regarding compilation failures in the llama.cpp project, often due to specific arguments or outdated toolkits. Users have suggested avoiding certain arguments or upgrading toolkits to resolve these errors.
- Performance Problems: Users have experienced significant performance issues with the llama.cpp project, such as slow inference times and degraded performance on specific hardware. These problems have prompted users to seek explanations and solutions for the discrepancies.
- Feature Requests: There are multiple feature requests aimed at enhancing the functionality of the llama.cpp project, including support for new operations, improved user interfaces, and additional functionalities for handling tasks and models.
- Bugs in Model Execution: Various bugs have been reported in the execution of models within the llama.cpp project, including issues with repetitive text generation, empty inputs, and inconsistent responses. Users have provided detailed reports and suggestions for potential fixes.
- Backend and Compatibility Issues: Users have encountered problems with backend compatibility and functionality, particularly with Vulkan and OpenCL, leading to crashes and performance issues. These issues highlight the need for better support and configuration options.
- Model Conversion and Quantization Errors: Errors have been reported during model conversion and quantization processes, often resulting in crashes or incorrect outputs. Users have detailed these issues and suggested improvements to the conversion scripts and quantization methods.
- Runtime and Execution Failures: Users have experienced runtime errors and execution failures in the llama.cpp project, often due to missing files or unsupported features. These issues have led to requests for better error handling and feature support.
2.4 Closed Issues
This section lists, groups, and then summarizes issues that were closed within the last week in the repository. This section also links the associated pull requests if applicable.
Issues Closed This Week: 24
Summarized Issues:
- Feature Requests for Model Support: Several issues involve requests for adding support to various models in the llama.cpp project. These include the Zyphra/Zamba2-2.7B model, DeciLMForCausalLM, and Alibaba's Macro-o1 model, each promising performance improvements or advanced features. Users are seeking guidance on model conversion and support, highlighting the need for efficient resource utilization and compatibility with existing systems.
- Compilation and Installation Issues: Various issues report problems with compiling or installing components of the llama.cpp project. These include errors related to missing package configurations, Vulkan shader compilation failures, and incorrect directory placements in the gguf package, causing conflicts and build failures across different systems.
- Performance and Optimization Concerns: Performance issues are highlighted in several reports, such as degraded throughput on macOS with concurrent requests and excessive memory usage in CUDA kernels. These issues prompt discussions on potential optimizations and improvements to enhance efficiency and resource management.
- Bugs in Functionality and Tokenization: Multiple issues describe bugs affecting the functionality of the llama.cpp project, including incorrect tokenization, broken static file serving, and unexpected token insertion. These bugs lead to discrepancies in expected outputs and hinder the usability of certain features.
- Feature Requests for Enhanced Usability: Users have requested new features to improve the usability of the llama.cpp project, such as the ability to cancel prompt processing and send prompts via GET requests. These requests aim to address bottlenecks and enhance the flexibility of the system for various use cases.
- Model Conversion and Compatibility Issues: Issues related to model conversion and compatibility are reported, including errors with vocabulary during model loading and discrepancies in layer distribution across GPUs. These problems highlight the challenges in ensuring seamless integration and efficient resource allocation.
- Miscellaneous Technical Challenges: Other technical challenges include segmentation faults, outdated workarounds, and hardware-specific optimizations. These issues require careful troubleshooting and updates to maintain compatibility and performance across different environments.
2.5 Issue Discussion Insights
This section will analyze the tone and sentiment of discussions within this project's open and closed issues that occurred within the past week. It aims to identify potentially heated exchanges and to maintain a constructive project environment.
Based on our analysis, there are no instances of toxic discussions in the project's open or closed issues from the past week.
III. Pull Requests
3.1 Open Pull Requests
This section provides a summary of pull requests that were opened in the repository over the past week. The top three pull requests with the highest number of commits are highlighted as 'key' pull requests. All other pull requests are grouped based on similar characteristics for easier analysis.
Pull Requests Opened This Week: 17
Key Open Pull Requests
1. contrib : add naming guidelines: This pull request introduces and expands upon naming guidelines for the project, including the addition of a _t suffix guideline, reorganization of coding guidelines into the correct section, and minor rewording, as detailed in multiple commits linked to the discussion in another pull request.
- URL: pull/11177
- Merged: No
- Associated Commits: 610a03a8c447d1b119ae038f2d89e2dd7c5dfca2, e7bc61bc53af790fe59d7265a560ba60e58b43bd, 7fd17ba7cc15ef9e263e9acd9df6a4e767aad2ee, da47eb0650e27946da02c0858b657348aff9665d, f44939a6eba3ab49ae28beb140b24d7248fcc295, 7637216d3f104ea3900350bb4aa6b674e7eded54, 10ef6c1853f93cde09392f01adf133418a591809, 31a44094ad818f6d1472777bc6bbc02a82eaf295, b6f9640157aa6046e2312f072cf616f7af55cc73
2. llama : functions -> methods: This pull request refactors the llama project by transitioning functionality from struct llama_model to struct llama_vocab, moving tensor data loading to src/llama-model.cpp, and updating the API for improved naming consistency, including making struct llama_vocab public and modifying various API calls to use it instead of struct llama_model.
- URL: pull/11110
- Merged: No
- Associated Commits: 609ec7e0a0961208702e65710e250bf1d67a31c2, c725f691ea291f36cfa52779922cb29d7770915c, 45aab64e93d11aa08ba1c722fc0c65c1ff458364, a857dc50af223cf721f2868f8395a58b12fc4117, aeeb9420a32699f5f55afc5471bcae61bcc8e473, 6efee8cb888163b4c50bff406b2556537a9a9b49, 6df37bc28b7b3a735e387529112d4bad48f0a69a, 6540935bca0d3a2e03368df3d2269270ebb173e5
3. ggml-cuda : add TQ2_0 kernels, for ternary inference on GPU: This pull request introduces CUDA kernels for the TQ2_0 ternary quantization type to enable ternary inference on GPUs, enhancing performance by implementing matrix multiplication and dequantization using cuBLAS, and addressing previous limitations in handling matrix multiplication quantization (mmq) compared to similar efforts, while also providing performance benchmarks on NVIDIA GPUs.
- URL: pull/11183
- Merged: No
- Associated Commits: 970b5ab7ca1a335b178f6831534b066d529c90c5, fb43d5e8b57120e0dba713598116136bc3777e8c, 983aa09b5cd420e697d91ef3e08e75614f7357f3, f5fddb6d24c4ac4aae1a9bcd9ec222f739b0fc65
Other Open Pull Requests
- Server Web UI Enhancements: This topic covers improvements to the server Web UI, specifically enabling the pre-filling of the textarea with a message or query via URL parameters. These enhancements allow for auto-focus and automatic response generation, facilitating quick testing and demonstrations.
- Vulkan Shader Support for Quantized Formats: The pull request introduces support for copying data from the f32 format to various quantized formats using Vulkan shaders. It is based on existing CUDA implementations and addresses the conversion process and assumptions about data contiguity.
- Tag-Based Repository Referencing in llama-cli: This feature allows the llama-cli tool to support tag-based repository referencing, similar to Ollama. Users can specify models from Hugging Face using a tag-based syntax, which automatically suggests the appropriate GGUF file.
- GitHub Actions Workflow for visionOS: A new GitHub Actions workflow is introduced to facilitate building on visionOS using CMake and Xcode. It also removes the explicit setting of
_XOPEN_SOURCEto potentially resolve build failures on visionOS.
- New Test Option in llama-bench Tool: The llama-bench tool now includes a new test option
-gpto measure the token generation rate after processing a prompt of a specified length. This test focuses solely on token generation rate without considering prompt length and processing time.
- Gated Linear Attention Kernel in SYCL Backend: This pull request introduces a gated linear attention kernel to the SYCL backend, translating logic from an existing CUDA kernel. Initial tests have passed, but further testing on an Nvidia GPU is suggested due to memory constraints.
- Optimization in Vulkan Component: An optimization is proposed for the coopmat2 q2_k dequant function in the Vulkan component. This aims to enhance performance by approximately 5% for Q2_K models used in stable-diffusion/flux.
- GGML Compilation on macOS with GCC: This pull request resolves compatibility issues related to the inclusion of
pthread.hand its dependency on the Apple-specificqos.hheader. It notes that the Metal backend remains incompatible with GCC due to Objective-C compilation challenges.
- Enhancements to OuteTTS: A feature is introduced to enhance the accuracy of OuteTTS by using guide tokens. This improves text-to-speech recitation over long input sequences, addressing incoherent output issues as input length increases.
- Instruction Set Limitation in GGML: The pull request proposes limiting the instruction set to SSE4.1 to align with the software's target requirements. This includes previous instruction sets to ensure compatibility as part of integrating the ProstT5 protein language into Foldseek.
- Fixes in ggml-cuda Component: This pull request ensures that the
cuGetErrorStringfunction is not used when theGGML_CUDA_NO_VMMmode is enabled. It is part of the integration of the ProstT5 protein language into the Foldseek project.
- CUDA GET_ROWS Operation Fix: An issue with the CUDA GET_ROWS operation failing for long sequences is addressed. The fix is implemented specifically for the _float operation as part of integrating the ProstT5 protein language into Foldseek.
- CUDA Build Options for CI: Options are introduced to compile CUDA builds without mmq and flash attention to reduce CI compile times and binary sizes. This is part of integrating the ProstT5 protein language into Foldseek and upstreaming fixes to the ggml library.
- CMake Flag for Preventing Shadowing: The
-Wshadowflag is enabled in CMake for C++ code to prevent shadowing of class members. Tasks include fixing existing warnings and checkingclang-tidysupport.
3.2 Closed Pull Requests
This section provides a summary of pull requests that were closed in the repository over the past week. The top three pull requests with the highest number of commits are highlighted as 'key' pull requests. All other pull requests are grouped based on similar characteristics for easier analysis.
Pull Requests Closed This Week: 55
Key Closed Pull Requests
1. [swift] add module omnivlm : This pull request aims to add a new module called "omnivlm" to the project, which includes support for various features such as ggml, omni-audio, and qwen2-audio, updates to C++17 for compilation, and the addition of examples in C++ and Python, while also addressing issues like memory leakage, build errors, and compatibility with different platforms like iOS and Android.
- URL: pull/11171
- Merged: No
- Associated Commits: 5f81588780339fd58c172591aa8273a198a20bca, 3a3552632aa4e9529a9bff1030db37c153fd4a42, 4a29bca867e2601a2e69e007640ac1abb9f3a381, c7b912bdca66ad5cc3edef66117d35837006ff2e, f0d1c4fa1c06c1bc9cd7a42b83e32f73e69e6fbe, 9e67ef75b46b4d267b9df4ac6c1f232681470a4c, 4bdc70aaac8884df987f4b079b3d063f2f31e076, d277c674ae20a3a1277f71a14a2956bf5b3196ca, 995baefeed7407cdbaf4e8aef4debfeb2621a12b, a4747b2edb90b9fbf8cb7c3108ba973fc79d7152, 6f1ed6e5cb1e8003b1b7146bc5aaf1e525bf9096, 141968108994905dc481863b75e0837cb693f5e3, d42e0371f84b413c25511328d75f079962c6fbbb, 05853eb861d522cc51c450efbabdc1470118cf5b, 91b3cafbb5acee59ad5cf94a05c952c5177d2969, d6c0627d31866d865f16e862a5456f3bb8857dfd, 983b4625ef51503853979ddbedd7df14084faadd, b535cd941e657ac1984d8022dd5f0c98f2b9e265, 38c6fa3b8fb6c88075102fd859d04eaea27aa87c, 22da7bc379b491680a7db25600c14f8addfbc93d, 5574bda471c4ddfa263438f5ca978ccad2e85903, b24a409e22dc49daa7f7cb422492281403dfb239, 6a4cf0b983195c7f32251e6d550f3c65b854ca6b, 5edadffd887f2b72ebc93134e7ad76082757b75a, 20b9f02cee483d09d15832c35e6117e5a020f517, 3dfac7817f8f40562b559e877b50b104d697bcf8, df5841b6b8ac0740b1e2310f9e8ae609d6290b3c, 86c2233a38c963b2b9112994a9f9c3890b6522f0, 400fc2a4b09d37d3256c803d8f4292385285dad6, b17684efb3a1da600bbde26cd6554f74e964af2f, 16c22471e88a9c8bd2049be890642ba496ee496f, 3d9c63a3ffc27fc10c910e3b71b89c87008926d7, eb6d54679e518edebf2ee8b5f39c0dcb613811cc, 8c417282d52e9b8931ff3e93ff6382b85be81d87, d5df53658f587fe1bd0de22376b3dadc055eb713, ecfe0b487f49d52e0d9012b89ca40d07b3f38b41, 667a6d9838931f2aaab95ee9d70142dc1ba057bd, d04e354f2f55510e7a4c9dfa4659e4861d7290d3, 21bc833273721000501fd8c742450731db6d4709, 6f0e8c3ee6be4695863545f786bc9159548eed31, 7cf07df5e20c12624376656ce81c06b621cbb3a6, 362bdf32924b8a0c00c8998b9a9f274977e07b80, 5f2d95849269f4b847afc9563de763ff5daf2afe, 55953d35a4aab2ffa96fde090bdd48ff7e385f16, 82dbdbdb40b3b2e4a945d23e9e952d4e463d598e, 89bcf5a6d918c6dd0987432b859680d3b8548929, 4e80184c321b9c04866735ca6f4545eb15919e4a, 98297afbd590d511b90c7e2b6986f6d8788c25a4, bb33473f08db604e1f30334366032f0904e2a722, fc25544867f591e0831dea493675ff0d8775dfc9, b9845b4f63bb50eb16c1d510706ddb885b380975, aad0167bc3accc17ec80db5225576e4130383cc7, 8e2e6304057af44e66c0c3a123ca798dc4d25a55, e4ca946c48ee6e1a848cf88e5f81680179b0fbf5, 25190fefa29d946ba28f92a01599c228f0c66e9d, fe792d62b1bed14c6dbc48421840473eae2a08ae, fd2c58286aaeb4ed51d6b963344a6d2584e25ab5, 7589158595091a88b7844c83569f68c780469d5b, bbf1aaa7eddb2eccd3a955f476a4e07475cae3be, 460212ac2a61cd24f479bba145a9e652f01f31b3, fe8c7b45fd5eca1c38a09c257ebf8cf1ccae3a4a, 43f41a4c00086d163463b79a3bc55d1656b6bf2b, 3479f516ea55c9a278986e9a300a163979be4177, 809db95990cd53c62bce94afb9ad99848d770413, a2c53052bdb74dde139ed61b3f4e724e3848b7d5, 661b3f718c4b31793875f4c1d310ee12076b4ae3, 0b15d2d7452f4cdbb2295bec1979fe9194ae7400, 71b563ec9a4ab9c06fb23d1b72ea3688d8843bf4, 97267e60bdfa06126899bee025a0d52f3b36f2e9, be54cb02ff14354ac78dd8ec8a9efa170475b00d, ca7e8ef19e1e3ca1558d64e184218e83294ebb5d, 07c7ff3e4a0e067a78e61bad11964376aec8c9da, b86cdedb7e5d0b9b2fe61404c39010a149da99be, b2958b33ddd4c8f13c98fb1c1249ac067769df91, 64a6001a1a408129eb510f49840947876220c5fa, 5962b506bab3f46821e0fb74bcbe224cb6b10b68, 1487d32b46a210c5619886af8fe24c93091f7ca0, d3eeeae2185b8f1cb626421ae96fb8af76b2ce82, 61777707ca6aecf077d35c7439dd263342a36226, 91ab9ed858aabb7eea7ddcc0ec6843367404a148
2. Add support for QRWKV6 hybrid models & slight optimization for RWKV6: This pull request introduces support for QRWKV6 hybrid models, which combine the Qwen2.5 architecture with RWKV6 to convert Qwen2.5-32B-Instruct model's QKV attention into RWKV6 linear attention, along with optimizations for RWKV6 such as graph simplification and concatenated lerp weights to reduce CPU overhead during inference.
- URL: pull/11001
- Merged: Yes
- Associated Commits: f298f0397084dcc50e1a1f2dbdb1ed36daf10687, 385b611d4590c3b761e97d6fd99f710c5b5a7c85, fab0aa7b1a52e4aebe484878a35ba372ad821b5f, bc930cd59a3c245da4c9f47f1458e65bead1e92d, f2c1a5c91892656c3b399fb205017b519e1e94ca, aaa870e80eea3fdda0be7fed4ed28d5c5ec8910a, 00930e6fe5a64baf3faccab9b12ef2638e3c6a60, 08cf56060bc3bbe55e9a40db423b36567bfd6f4b, 331581b2e3d46cac285b34447ec8ad15cb212f95, aed0afb40884d0066ea64046fdd0d70575accdf2, d8a304c2ef86a5449bb075bb707fbde66b3b4ad4, 324afba5ccac7250b251f4cff31c812e2e86a3fc
3. lora : improve compat with mergekit-extract-lora: This pull request enhances compatibility with mergekit-extract-lora by updating the convert_lora_to_gguf.py script to retain specific tensors in the GGUF output and adding support for token_embd in llama.cpp, facilitating the conversion of fine-tuned models into LoRA adapters with minimal quality degradation.
- URL: pull/11131
- Merged: Yes
- Associated Commits: 93fbfd022cfdabb48807de7de2a99ec038d43b66, e444b8e0c2662036111e123b234c59595775f216, b37af1424ac21f863439eb4774da0455e7094620, 0615cdd7a49fb06d67c13290e9664195d0a96b29, 11e0c733acf46c43ca344d957144043a4b2842ef, f564e0212e644f18e9cba1bcdd3e278115e3c2c6, 65a431dbbc0b9326918fd0837462062eaf261ff3, a1f82956f76e61f7abae9776af8281db1bf1f426
Other Closed Pull Requests
- Bug Fixes and Improvements in GGUF and SYCL: Several pull requests focused on enhancing the GGUF code and SYCL backend, including refactoring GGUF into C++, fixing metadata size handling, and improving tensor operations in SYCL. These changes aim to improve compatibility, error handling, and performance across different platforms.
- Vulkan and Shader Compatibility: Multiple pull requests addressed issues related to Vulkan shader generation and compatibility, such as fixing hardcoded paths and handling platforms without certain extensions. These updates ensure that the project can be built and run on a wider range of systems.
- API and Naming Consistency: Several pull requests were made to update API names and improve naming conventions, ensuring consistency across the project. These changes help maintain a clear and organized codebase, making it easier for developers to understand and contribute.
- Enhancements in Tokenization and Vocabulary Management: Pull requests focused on improving tokenization processes and managing vocabulary size parameters, which included avoiding unnecessary string copies and consolidating vocabulary information. These enhancements aim to optimize performance and reduce redundancy.
- New Features and Support for Architectures: New features such as the IQ4_NL_4_4 format and PhiMoE architecture were introduced, providing improved accuracy and support for multilingual models. These additions expand the project's capabilities and enhance its applicability to diverse use cases.
- Continuous Integration and Build System Updates: Updates to the CI configuration and build system were made to improve security, stability, and compatibility with different environments. These changes ensure that the project remains robust and reliable during development and deployment.
- Documentation and User Interface Enhancements: Improvements were made to documentation and the web UI, including adding tooltips and a README.md file for better user guidance. These enhancements aim to improve user experience and accessibility of the project's features.
- Performance Improvements and Optimizations: Pull requests focused on performance improvements, such as introducing an INT8 implementation for matrix multiplication and optimizing BF16 support. These changes enhance the efficiency and speed of computations across various hardware configurations.
3.3 Pull Request Discussion Insights
This section will analyze the tone and sentiment of discussions within this project's open and closed pull requests that occurred within the past week. It aims to identify potentially heated exchanges and to maintain a constructive project environment.
-
contrib : add naming guidelines
- Toxicity Score: 0.55 (Frustration, defensiveness, persistent criticism.)
- This GitHub conversation involves multiple users discussing the addition of naming guidelines, with user1 expressing dissatisfaction over the lack of clarity in user2's explanations. User2 responds defensively, leading to a tense exchange. User3 attempts to mediate by suggesting a compromise, but user1 remains unconvinced, maintaining a critical tone. The conversation is marked by frustration and defensiveness, with user1's persistent criticism being a trigger for tension.
-
- Toxicity Score: 0.55 (Defensive responses, unresolved criticism, mediation attempts.)
- This GitHub conversation involves username1 expressing dissatisfaction with username2's proposed changes, leading to a defensive response from username2. The tone becomes tense as username3 attempts to mediate, but username1 remains critical, escalating the situation.
IV. Contributors
4.1 Contributors
Active Contributors:
We consider an active contributor in this project to be any contributor who has made at least 1 commit, opened at least 1 issue, created at least 1 pull request, or made more than 2 comments in the last month.
If there are more than 10 active contributors, the list is truncated to the top 10 based on contribution metrics for better clarity.
| Contributor | Commits | Pull Requests | Issues | Comments |
|---|---|---|---|---|
| ggerganov | 160 | 34 | 4 | 90 |
| ngxson | 77 | 16 | 3 | 85 |
| slaren | 14 | 8 | 0 | 66 |
| netrunnereve | 51 | 3 | 0 | 16 |
| jeffbolznv | 13 | 7 | 0 | 47 |
| 0cc4m | 6 | 3 | 0 | 38 |
| JohannesGaessler | 15 | 4 | 0 | 28 |
| qnixsynapse | 20 | 4 | 0 | 16 |
| Djip007 | 5 | 0 | 0 | 32 |
| fairydreaming | 0 | 3 | 0 | 27 |