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llama.cpp b12000 አውርድ

LLM inference in C/C++

ይህ የቆየ ስሪት ነው። የአሁኑ ስሪት b9994 ነው። llama.cpp b9994 · የተለቀቀበት:

የመጫኛ ፋይሎች b12000

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የልቀት ማስታወሻዎች

Quant: OCP FP8 E4M3 support (#27512)
- WIP OCP FP8 E4M3 support
- Fix python type-checker
- Materialize input_scales also for FP8 when converting
- Fix conversion of https://huggingface.co/RedHatAI/Qwen3.8-27B-NVFP4
1. Per row FP8 wrongly fell to NVFP4 conversion, as NVFP4 checked on
dims alone. Also check on dtype for FP8
2. Need to reshape FP8 QKV projections scales in the same way that
weights are reshaped
- Allow remaining FP8 tensors to be dequantized during conversion
- Allow tensor-strategy for FP8-only compressed-tensor ckpts
- Fix and test gguf-py behavior for FP8_E4M3
- Disallow QKV-fusion for FP8 temporarily
- Fix conversion of fused qkvz & FP8 for Qwen3-Next
- Avoid fusing FP8 for --fuse-gate-up-exps as we may have different ws
- Emit warnings when not fusing FP8 during conversion
- More FP8 conversion fixes
- Add supported for strided copies to/from FP8 in CPU
- remove unneeded scratch buffer from FP8 cpu cpy/dup path
- add explanatory comments and TODOs
- Add dedicated encoder and decoder tests for FP8
- Whitelist ggml_op_get_rows in metal instead of blacklisting
required to fix failing CI, and white-listing should be more
future-proof than adding FP8 to the black-list
https://github.com/ggml-org/llama.cpp/actions/runs/38433916498/job/115422880633?pr=27512
- Fix more conversion bugs
- Defer weight materialization during conversion
- Blacklist fp8 in metal backend instead of white-list
- Adjust indents
- Fix lint + execute tests
- Add fast CPU kernel for F8_E4M3
- Conversion fixes
- Fix remaining gaps
- Enable tied weights with shared scales
- Make mandatory-F32 rules apply to FP8 during conversion
- Fix python type checks
https://github.com/ggml-org/llama.cpp/actions/runs/39765670052/job/119780379595?pr=27512
- Fix kaleidai unit-test failures
https://github.com/ggml-org/llama.cpp/actions/runs/39765670125/job/119780383150
- Relax numeric precision constraints for pre-check
- Leave fast-FP8 CPU on RISC-V for follow-up
We already exclude arm from the fast-path
- Allow output scale tensors to be located in any gguf shard
- Move test_conversion_fp8.py test execution to behavior-check.yaml
- Apply batched suggestions from code review
Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co
- Move mixed compressed-tensor logic into dequant_fp8 + add unit-tests for it
- Install all requirements also on Windows for behavior-check
Fixes https://github.com/ggml-org/llama.cpp/actions/runs/40535852590/job/122300758223?pr=27512
- Unmap lazy tensors before clean-up in Windows
Should fix https://github.com/ggml-org/llama.cpp/actions/runs/40539797824/job/122314782459?pr=27512
- LF line endings
https://github.com/ggml-org/llama.cpp/actions/runs/40539798168/job/122314791118?pr=27512
- Extract FP8 tests from llama-arch to its own test-fixture
See #27512 (comment)
- Update gguf-py/gguf/scripts/gguf_convert_endian.py
Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co
Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co
Website:
- https://llama.app
Attestations:
- https://github.com/ggml-org/llama.cpp/attestations/61605392
macOS/iOS:
- macOS Apple Silicon (arm64)
- macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED
- macOS Intel (x64)
- iOS XCFramework
Linux:
- Ubuntu x64 (CPU)
- Ubuntu arm64 (CPU)
- Ubuntu s390x (CPU)
- Ubuntu 26.04 s390x (CPU)
- Ubuntu 26.04 s390x (zDNN)
- Ubuntu x64 (Vulkan)
- Ubuntu arm64 (Vulkan)
- Ubuntu x64 (CUDA 12) - CUDA 12.8 libraries
- Ubuntu x64 (CUDA 13) - CUDA 13.4 libraries
- Ubuntu arm64 (CUDA 13) - CUDA 13.4 libraries
- Ubuntu x64 (ROCm 10.0)
- Ubuntu x64 (OpenVINO)
- Ubuntu x64 (SYCL FP32)
- Ubuntu x64 (SYCL FP16)
- Linux arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide
Android:
- Android arm64 (CPU)
- Android arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide
Windows:
- Windows x64 (CPU)
- Windows arm64 (CPU)
- Windows arm64 (OpenCL Adreno)
- Windows x64 (CUDA 12) - CUDA 12.4 DLLs
- Windows x64 (CUDA 13) - CUDA 13.4 DLLs
- Windows arm64 (CUDA 13) - CUDA 13.4 DLLs
- Windows x64 (Vulkan)
- Windows arm64 (Vulkan)
- Windows x64 (OpenVINO)
- Windows x64 (SYCL)
- Windows x64 (ROCm 10.0)
openEuler:
- DISABLED
- openEuler x86 (310p)
- openEuler x86 (910b, ACL Graph)
- openEuler aarch64 (310p)
- openEuler aarch64 (910b, ACL Graph)
UI:
- UI

https://github.com/ggml-org/llama.cpp/releases/tag/b12000

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