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https://github.com/LostRuins/koboldcpp.git
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e7e4df031b
* llama : ggml-backend integration * ggml-backend : add names to buffers * fix unmap after loading * batched-bench : add tensor_split param * llama : check for null tensor_split * ggml-backend : increase GGML_MAX_BACKENDS * improve graph splitting, partial fix for --no-kv-offload * cuda : add ggml-backend split buffer support * cuda : do not create buffer types for devices that don't exist (fixes usage without CUDA devices available) * ggml : fix null backend dereference (#4807) * ggml : fix null backend dereference * ggml : also check ggml_backend_is_cpu * test-backend-ops : check buffer allocation failures * llama : add cparam (split_mode) and command line argument (--split-mode, -sm) to configure the split mode (none, layer or row) * ggml : fix mul_mat_id work size * llama : rewrite session kv load/set without graphs * minor * llama : only initialize used backends, free backends on context free * llama : abort ctx if cuda backend init fails * llama : rewrite lora with ggml-backend and compute on CPU ggml-ci * llama : only map to a backend buffer the region of the file mapping containing the tensors used in the buffer * opencl : add ggml-backend buffer type * cuda : only use batched_cublas with batched mat muls (fixes fp16 tg perf) * llama : on Metal, by default offload the full model ggml-ci * metal : page align the data ptr (#4854) * Apply suggestions from code review Co-authored-by: Johannes Gäßler <johannesg@5d6.de> * cuda : fix split buffer free * address review comments * llama-bench : add split-mode parameter * fix whitespace * opencl : fix double initialization * server : add --split-mode parameter * use async copy and compute to improve multi-gpu performance ggml-ci * use async memcpys to copy the graph outputs to the CPU * fix opencl * use a host buffer for the cpu compute buffer for faster copies to the gpu --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: Johannes Gäßler <johannesg@5d6.de> |
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| .. | ||
| baby-llama | ||
| batched | ||
| batched-bench | ||
| batched.swift | ||
| beam-search | ||
| benchmark | ||
| convert-llama2c-to-ggml | ||
| embedding | ||
| export-lora | ||
| finetune | ||
| gguf | ||
| imatrix | ||
| infill | ||
| jeopardy | ||
| llama-bench | ||
| llama.swiftui | ||
| llava | ||
| lookahead | ||
| lookup | ||
| main | ||
| main-cmake-pkg | ||
| metal | ||
| parallel | ||
| passkey | ||
| perplexity | ||
| quantize | ||
| quantize-stats | ||
| save-load-state | ||
| server | ||
| simple | ||
| speculative | ||
| tokenize | ||
| train-text-from-scratch | ||
| alpaca.sh | ||
| base-translate.sh | ||
| chat-13B.bat | ||
| chat-13B.sh | ||
| chat-persistent.sh | ||
| chat-vicuna.sh | ||
| chat.sh | ||
| CMakeLists.txt | ||
| gpt4all.sh | ||
| json-schema-to-grammar.py | ||
| llama.vim | ||
| llama2-13b.sh | ||
| llama2.sh | ||
| llm.vim | ||
| make-ggml.py | ||
| Miku.sh | ||
| reason-act.sh | ||
| server-llama2-13B.sh | ||