mirror of
https://github.com/dogkeeper886/ollama37.git
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ef14fb5b26
This commit represents a complete rework after pulling the latest changes from official ollama/ollama repository and re-applying Tesla K80 compatibility patches. ## Key Changes ### CUDA Compute Capability 3.7 Support (Tesla K80) - Added sm_37 (compute 3.7) to CMAKE_CUDA_ARCHITECTURES in CMakeLists.txt - Updated CMakePresets.json to include compute 3.7 in "CUDA 11" preset - Using 37-virtual (PTX with JIT compilation) for maximum compatibility ### Legacy Toolchain Compatibility - **NVIDIA Driver**: 470.256.02 (last version supporting Kepler/K80) - **CUDA Version**: 11.4.4 (last CUDA 11.x supporting compute 3.7) - **GCC Version**: 10.5.0 (required by CUDA 11.4 host_config.h) ### CPU Architecture Trade-offs Due to GCC 10.5 limitation, sacrificed newer CPU optimizations: - Alderlake CPU variant enabled WITHOUT AVX_VNNI (requires GCC 11+) - Still supports: SSE4.2, AVX, F16C, AVX2, BMI2, FMA - Performance impact: ~3-7% on newer CPUs (acceptable for K80 compatibility) ### Build System Updates - Modified ml/backend/ggml/ggml/src/ggml-cuda/CMakeLists.txt for compute 3.7 - Added -Wno-deprecated-gpu-targets flag to suppress warnings - Updated ml/backend/ggml/ggml/src/CMakeLists.txt for Alderlake without AVX_VNNI ### Upstream Sync Merged latest llama.cpp changes including: - Enhanced KV cache management with ISWA and hybrid memory support - Improved multi-modal support (mtmd framework) - New model architectures (Gemma3, Llama4, Qwen3, etc.) - GPU backend improvements for CUDA, Metal, and ROCm - Updated quantization support and GGUF format handling ### Documentation - Updated CLAUDE.md with comprehensive build instructions - Documented toolchain constraints and CPU architecture trade-offs - Removed outdated CI/CD workflows (tesla-k80-*.yml) - Cleaned up temporary development artifacts ## Rationale This fork maintains Tesla K80 GPU support (compute 3.7) which was dropped in official Ollama due to legacy driver/CUDA requirements. The toolchain constraint creates a deadlock: - K80 → Driver 470 → CUDA 11.4 → GCC 10 → No AVX_VNNI We accept the loss of cutting-edge CPU optimizations to enable running modern LLMs on legacy but still capable Tesla K80 hardware (12GB VRAM per GPU). 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
44 lines
2.3 KiB
Diff
44 lines
2.3 KiB
Diff
From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
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From: Michael Yang <mxyng@pm.me>
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Date: Mon, 16 Sep 2024 15:53:13 -0700
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Subject: [PATCH] pretokenizer
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allow for an unset pretokenizer with a warning in the
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logs instead of throwing an error
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---
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src/llama-vocab.cpp | 14 +++-----------
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1 file changed, 3 insertions(+), 11 deletions(-)
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diff --git a/src/llama-vocab.cpp b/src/llama-vocab.cpp
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index 7fffd171..0b6edaf4 100644
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--- a/src/llama-vocab.cpp
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+++ b/src/llama-vocab.cpp
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@@ -1812,16 +1812,7 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
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if (type == LLAMA_VOCAB_TYPE_BPE) {
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add_space_prefix = false;
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clean_spaces = true;
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- if (tokenizer_pre.empty()) {
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- LLAMA_LOG_WARN("%s: missing pre-tokenizer type, using: 'default'\n", __func__);
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- LLAMA_LOG_WARN("%s: \n", __func__);
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- LLAMA_LOG_WARN("%s: ************************************ \n", __func__);
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- LLAMA_LOG_WARN("%s: GENERATION QUALITY WILL BE DEGRADED! \n", __func__);
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- LLAMA_LOG_WARN("%s: CONSIDER REGENERATING THE MODEL \n", __func__);
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- LLAMA_LOG_WARN("%s: ************************************ \n", __func__);
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- LLAMA_LOG_WARN("%s: \n", __func__);
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- pre_type = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
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- } else if (tokenizer_pre == "default") {
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+ if (tokenizer_pre == "default") {
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pre_type = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
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} else if (
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tokenizer_pre == "llama3" ||
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@@ -1992,7 +1983,8 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
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pre_type = LLAMA_VOCAB_PRE_TYPE_GROK_2;
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clean_spaces = false;
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} else {
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- throw std::runtime_error(format("unknown pre-tokenizer type: '%s'", tokenizer_pre.c_str()));
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+ LLAMA_LOG_WARN("%s: missing or unrecognized pre-tokenizer type, using: 'default'\n", __func__);
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+ pre_type = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
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}
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} else if (type == LLAMA_VOCAB_TYPE_SPM) {
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pre_type = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
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