Step-3.5-Flash-GGUF
6.3K
29
ik_llama.cpp
by
ubergarm
Language Model
OTHER
New
6K downloads
Early-stage
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Quick Summary
AI model with specialized capabilities.
Code Examples
IQ5_K 136.891 GiB (5.970 BPW)bash
#!/usr/bin/env bash
custom="
# 45 Repeating Layers [0-44]
# Attention [0-44] GPU
blk\..*\.attn_gate.*=q8_0
blk\..*\.attn_q.*=q8_0
blk\..*\.attn_k.*=q8_0
blk\..*\.attn_v.*=q8_0
blk\..*\.attn_output.*=q8_0
# First 3 Dense Layers [0-2] GPU
blk\..*\.ffn_down\.weight=q8_0
blk\..*\.ffn_(gate|up)\.weight=q8_0
# Shared Expert Layers [3-44] GPU
blk\..*\.ffn_down_shexp\.weight=q8_0
blk\..*\.ffn_(gate|up)_shexp\.weight=q8_0
# Routed Experts Layers [3-44] CPU
blk\..*\.ffn_down_exps\.weight=iq6_k
blk\..*\.ffn_(gate|up)_exps\.weight=iq5_k
# Non-Repeating Layers
token_embd\.weight=q8_0
output\.weight=q8_0
"
custom=$(
echo "$custom" | grep -v '^#' | \
sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
)
numactl -N ${SOCKET} -m ${SOCKET} \
./build/bin/llama-quantize \
--custom-q "$custom" \
--imatrix /mnt/data/models/ubergarm/Step-3.5-Flash-GGUF/imatrix-Step-3.5-Flash-BF16.dat \
/mnt/data/models/ubergarm/Step-3.5-Flash-GGUF/Step-3.5-Flash-288x7.4B-BF16-00001-of-00009.gguf \
/mnt/data/models/ubergarm/Step-3.5-Flash-GGUF/Step-3.5-Flash-IQ5_K.gguf \
IQ5_K \
128Quick Startbashllama.cpp
# Clone and checkout
$ git clone https://github.com/ikawrakow/ik_llama.cpp
$ cd ik_llama.cpp
# Build for hybrid CPU+CUDA
$ cmake -B build -DCMAKE_BUILD_TYPE=Release -DGGML_CUDA=ON
$ cmake --build build --config Release -j $(nproc)
# Run full offload on >2 GPUs with `-sm graph` Graph Parallel
## https://github.com/ikawrakow/ik_llama.cpp/pull/1236
## https://github.com/ikawrakow/ik_llama.cpp/pull/1231
## https://github.com/ikawrakow/ik_llama.cpp/pull/1239
## https://github.com/ikawrakow/ik_llama.cpp/pull/1240
CUDA_VISIBLE_DEVICES="0,1" \
./build/bin/llama-server \
--model "$model" \
--alias ubergarm/Step-Fun-3.5-Flash \
-c 65536 \
-ger \
-sm graph \
-ngl 99 \
-ub 4096 -b 4096 \
-ts 47,48 \
--threads 1 \
--host 127.0.0.1 \
--port 8080 \
--jinja \
--no-mmap
# CPU-only Mainline llama.cpp Example
numactl -N "$SOCKET" -m "$SOCKET" \
./build/bin/llama-server \
--model "$model"\
--alias ubergarm/Step-3.5-Flash \
--ctx-size 65536 \
-ctk q8_0 -ctv q8_0 \
-ub 4096 -b 4096 \
--parallel 1 \
--threads 96 \
--threads-batch 128 \
--numa numactl \
--host 127.0.0.1 \
--port 8080 \
--no-mmap \
--jinjaDeploy This Model
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