Instructions to use tchbcb/MiniCPM5-2B-cpu-mixed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tchbcb/MiniCPM5-2B-cpu-mixed with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf tchbcb/MiniCPM5-2B-cpu-mixed # Run inference directly in the terminal: llama cli -hf tchbcb/MiniCPM5-2B-cpu-mixed
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tchbcb/MiniCPM5-2B-cpu-mixed # Run inference directly in the terminal: llama cli -hf tchbcb/MiniCPM5-2B-cpu-mixed
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf tchbcb/MiniCPM5-2B-cpu-mixed # Run inference directly in the terminal: ./llama-cli -hf tchbcb/MiniCPM5-2B-cpu-mixed
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf tchbcb/MiniCPM5-2B-cpu-mixed # Run inference directly in the terminal: ./build/bin/llama-cli -hf tchbcb/MiniCPM5-2B-cpu-mixed
Use Docker
docker model run hf.co/tchbcb/MiniCPM5-2B-cpu-mixed
- LM Studio
- Jan
- Ollama
How to use tchbcb/MiniCPM5-2B-cpu-mixed with Ollama:
ollama run hf.co/tchbcb/MiniCPM5-2B-cpu-mixed
- Unsloth Desktop
- Docker Model Runner
How to use tchbcb/MiniCPM5-2B-cpu-mixed with Docker Model Runner:
docker model run hf.co/tchbcb/MiniCPM5-2B-cpu-mixed
- Lemonade
How to use tchbcb/MiniCPM5-2B-cpu-mixed with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tchbcb/MiniCPM5-2B-cpu-mixed
Run and chat with the model
lemonade run user.MiniCPM5-2B-cpu-mixed-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
File size: 34,350 Bytes
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*
* Architecture: 42 layers, 2048 hidden, 16Q/2KV heads (GQA 8:1), 128 head_dim,
* 6144 MLP (SwiGLU), 130560 vocab, RoPE theta 5e6, RMSNorm eps 1e-6.
*
* Mixed precision (from GPQ8 file, per-tensor qtype):
* qtype=0 F32 : norms
* qtype=1 Q8 row : embed_tokens + lm_head (int8 + per-row fp32 scale)
* qtype=3 Q8_0 : layer 0 and 41 (8-bit, sensitive edge layers), 34B/32elem
* qtype=5 Q4_K : main body q/k/v/o/down + gate/up outside ternary range, 144B/256elem
* qtype=6 TERNARY : gate/up of layers 8..31, 3-value {-s,0,+s}, 18B/64elem
* (2B fp16 absmean scale + 8B bit0 stream + 8B bit1 stream;
* kernel: t = b0 - b1, y = x_scale * sum_b s_b * (S0-S1))
*
* Windows (MinGW-w64) port: CreateFileMapping mmap, QueryPerformanceCounter,
* no dlopen/weak-symbol LAL bridge, no pthread (OpenMP only).
*
* Build: gcc -O3 -march=native -fopenmp -I. -o prebuilt/minicpm_server.exe
* tools/server/minicpm_server.c -lm
* Run: prebuilt/minicpm_server.exe --weights C:/models/minicpm_mixed.bin
* --tokenizer C:/models/MiniCPM5-2B-cpu --prompt "..." --n 64 --threads 4
*/
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include <stdint.h>
#include <time.h>
#include <immintrin.h>
#include <omp.h>
#ifdef _WIN32
#include <windows.h>
#include <malloc.h>
#else
#include <sys/mman.h>
#include <sys/stat.h>
#include <fcntl.h>
#include <unistd.h>
#endif
/* === Architecture constants (MiniCPM5-2B, LlamaForCausalLM) === */
#define N_EMBD 2048
#define N_LAYER 42
#define N_HEAD 16
#define N_KV_HEAD 2
#define HEAD_DIM 128
#define N_Q_PER_KV (N_HEAD / N_KV_HEAD) /* 8 */
#define MLP_DIM 6144
#define VOCAB_SIZE 130560
#define N_CTX 2048
#define ROPE_THETA 5000000.0f
#define RMS_EPS 1e-6f
#define KV_DIM (N_KV_HEAD * HEAD_DIM) /* 256 */
#define Q_DIM (N_HEAD * HEAD_DIM) /* 2048 */
/* === SIMD wrappers (AVX2) === */
typedef __m256 v8f;
static inline float v8f_hsum(v8f v) {
__m128 hi = _mm256_extractf128_ps(v, 1);
__m128 lo = _mm256_castps256_ps128(v);
__m128 s = _mm_add_ps(lo, hi);
s = _mm_hadd_ps(s, s); s = _mm_hadd_ps(s, s);
return _mm_cvtss_f32(s);
}
/* === Reusable LAL SDK headers === */
#define XQ_MAX 6144 /* max in_dim across all matmuls = MLP_DIM */
#include "runtime/lal_q8_kernel.h"
#include "runtime/lal_q4k_kernel.h"
#include "runtime/lal_sampling.h"
#include "runtime/lal_dequant.h"
#include "runtime/lal_tokenizer.h"
#include "runtime/lal_simd_optim.h"
/* === Aligned alloc (portable) === */
static void *xalloc(size_t size, size_t align) {
#ifdef _WIN32
return _aligned_malloc(size ? size : 1, align);
#else
void *p = NULL;
if (posix_memalign(&p, align, size ? size : 1)) return NULL;
return p;
#endif
}
#define memalign(a, s) xalloc((s), (a))
/* === Timer === */
static double now_sec(void) {
#ifdef _WIN32
static LARGE_INTEGER freq = {0};
LARGE_INTEGER c;
if (!freq.QuadPart) QueryPerformanceFrequency(&freq);
QueryPerformanceCounter(&c);
return (double)c.QuadPart / (double)freq.QuadPart;
#else
struct timespec ts;
clock_gettime(CLOCK_MONOTONIC, &ts);
return ts.tv_sec + ts.tv_nsec * 1e-9;
#endif
}
/* === Windows read-only mmap === */
#ifdef _WIN32
static void *g_mmap_base;
static size_t g_mmap_size;
static void *win_mmap_ro(const char *path, size_t *out_size) {
HANDLE f = CreateFileA(path, GENERIC_READ, FILE_SHARE_READ, NULL,
OPEN_EXISTING, FILE_ATTRIBUTE_NORMAL, NULL);
if (f == INVALID_HANDLE_VALUE) { fprintf(stderr, "[!] cannot open %s\n", path); exit(1); }
LARGE_INTEGER sz;
GetFileSizeEx(f, &sz);
HANDLE m = CreateFileMappingA(f, NULL, PAGE_READONLY, 0, 0, NULL);
if (!m) { fprintf(stderr, "[!] CreateFileMapping failed\n"); exit(1); }
void *p = MapViewOfFile(m, FILE_MAP_READ, 0, 0, 0);
CloseHandle(m); CloseHandle(f);
if (!p) { fprintf(stderr, "[!] MapViewOfFile failed\n"); exit(1); }
*out_size = (size_t)sz.QuadPart;
return p;
}
#else
static void *g_mmap_base;
static size_t g_mmap_size;
static void *win_mmap_ro(const char *path, size_t *out_size) {
int fd = open(path, O_RDONLY);
if (fd < 0) { fprintf(stderr, "[!] cannot open %s\n", path); exit(1); }
struct stat st;
fstat(fd, &st);
void *p = mmap(NULL, st.st_size, PROT_READ, MAP_PRIVATE, fd, 0);
close(fd);
if (p == MAP_FAILED) { fprintf(stderr, "[!] mmap failed\n"); exit(1); }
madvise(p, st.st_size, MADV_SEQUENTIAL);
*out_size = st.st_size;
return p;
}
#endif
/* === Global state === */
static int g_n_threads = 1;
static float g_temperature = 0.8f;
static int g_top_k = 40;
static float g_rep_penalty = 1.1f;
static int g_recent[256], g_n_recent = 0;
/* === TERNARY AVX2 kernel (qtype=6) ===
* Block: 18 bytes / 64 elems = [2B fp16 scale][8B bit0][8B bit1]
* t_i = bit0_i - bit1_i in {-1,0,+1}; w_i ~= scale * t_i
* dot = x_scale * sum_b scale_b * (S0_b - S1_b), S = sum(bit * xq) (int32)
*/
static uint8_t g_bit_lut[256][8];
static void bit_lut_init(void) {
for (int b = 0; b < 256; b++)
for (int j = 0; j < 8; j++)
g_bit_lut[b][j] = (uint8_t)((b >> j) & 1);
}
/* binary dot over 32 elems: bits = 4 bytes (little-endian bitstream), xq = 32 int8 */
static inline int32_t bdot32(const uint8_t *bits, const int8_t *xq) {
uint8_t exp32[32] __attribute__((aligned(32)));
memcpy(exp32 + 0, g_bit_lut[bits[0]], 8);
memcpy(exp32 + 8, g_bit_lut[bits[1]], 8);
memcpy(exp32 + 16, g_bit_lut[bits[2]], 8);
memcpy(exp32 + 24, g_bit_lut[bits[3]], 8);
__m256i a = _mm256_loadu_si256((const __m256i *)exp32); /* unsigned 0/1 */
__m256i w = _mm256_loadu_si256((const __m256i *)xq); /* signed int8 */
__m256i r16 = _mm256_maddubs_epi16(a, w); /* 16 x int16 */
__m256i r32 = _mm256_madd_epi16(_mm256_set1_epi16(1), r16); /* 8 x int32 */
__m128i lo = _mm256_castsi256_si128(r32);
__m128i hi = _mm256_extractf128_si256(r32, 1);
__m128i s = _mm_add_epi32(lo, hi);
s = _mm_add_epi32(s, _mm_shuffle_epi32(s, _MM_SHUFFLE(1, 0, 3, 2)));
s = _mm_add_epi32(s, _mm_shuffle_epi32(s, _MM_SHUFFLE(2, 3, 0, 1)));
return _mm_cvtsi128_si32(s);
}
static inline float tern_dot_row(const uint8_t *row, const int8_t *xq,
float x_scale, int in_dim) {
int nb = in_dim / 64;
float acc = 0;
for (int b = 0; b < nb; b++) {
const uint8_t *blk = row + (size_t)b * 18;
uint16_t s16;
memcpy(&s16, blk, 2);
__m128i sh = _mm_set1_epi16((short)s16);
float s = _mm_cvtss_f32(_mm_cvtph_ps(sh));
const int8_t *xb = xq + (size_t)b * 64;
int32_t i0 = bdot32(blk + 2, xb) + bdot32(blk + 6, xb + 32);
int32_t i1 = bdot32(blk + 10, xb) + bdot32(blk + 14, xb + 32);
acc += s * (float)(i0 - i1);
}
return acc * x_scale;
}
static void parallel_matmul_ternary(float *y, const uint8_t *W,
const int8_t *xq, float x_scale,
int in_dim, int out_dim) {
int nb = in_dim / 64;
int row_stride = nb * 18;
if (g_n_threads <= 1 || out_dim < 1024) {
for (int r = 0; r < out_dim; r++)
y[r] = tern_dot_row(W + (size_t)r * row_stride, xq, x_scale, in_dim);
return;
}
#pragma omp parallel num_threads(g_n_threads)
{
int tid = omp_get_thread_num();
int n = omp_get_num_threads();
int chunk = (out_dim + n - 1) / n;
int start = tid * chunk;
int end = start + chunk;
if (end > out_dim) end = out_dim;
for (int r = start; r < end; r++)
y[r] = tern_dot_row(W + (size_t)r * row_stride, xq, x_scale, in_dim);
}
}
/* === Parallel Q8_0 matmul (packed 34B blocks, kernel quantizes x internally) === */
static void parallel_matmul_q8_0_w(float *y, const uint8_t *q8_0_W,
const float *x, int in_dim, int out_dim) {
if (g_n_threads <= 1 || out_dim < 1024) {
lal_matmul_q8_0(y, q8_0_W, x, NULL, in_dim, out_dim);
return;
}
int row_stride = (in_dim / 32) * 34;
#pragma omp parallel num_threads(g_n_threads)
{
int tid = omp_get_thread_num();
int n = omp_get_num_threads();
int chunk = (out_dim + n - 1) / n;
int start = tid * chunk;
int end = start + chunk;
if (end > out_dim) end = out_dim;
if (start < out_dim)
lal_matmul_q8_0(y + start, q8_0_W + (size_t)start * row_stride,
x, NULL, in_dim, end - start);
}
}
/* === Parallel Q4_K matmul (prepared) === */
static void parallel_matmul_q4_k_p(float *y, const uint8_t *q4k_W, const float *x,
int in_dim, int out_dim,
const int8_t *xq, const int16_t *bsums,
const int8_t *xq_arr, float x_scale) {
if (g_n_threads <= 1 || out_dim < 1024) {
lal_matmul_q4_k_prepared(y, q4k_W, x, NULL, in_dim, out_dim,
xq, bsums, xq_arr, x_scale);
return;
}
int row_stride = (in_dim / 256) * 144;
#pragma omp parallel num_threads(g_n_threads)
{
int tid = omp_get_thread_num();
int n = omp_get_num_threads();
int chunk = (out_dim + n - 1) / n;
int start = tid * chunk;
int end = start + chunk;
if (end > out_dim) end = out_dim;
if (start < out_dim)
lal_matmul_q4_k_prepared(y + start, q4k_W + (size_t)start * row_stride,
x, NULL, in_dim, end - start,
xq, bsums, xq_arr, x_scale);
}
}
static int8_t *g_wte_q; static float *g_wte_s; /* Q8row embedding */
static float *g_norm_f_w;
static int8_t *g_lm_head_q; /* Q8row lm_head */
static float *g_lm_head_s;
static float *g_x, *g_ln, *g_q, *g_k, *g_v, *g_attn_out, *g_proj, *g_mlp_out;
static float *g_logits;
static int8_t *g_xq_cache;
static float **kv_k, **kv_v;
static int g_rope_need = 0;
/* === RMSNorm / RoPE / GQA wrappers === */
static void qwen_rms_norm(float *out, const float *x, const float *w, int n) {
lal_rms_norm_simd(out, x, w, n, RMS_EPS);
}
static float g_rope_cos[N_CTX][HEAD_DIM / 2];
static float g_rope_sin[N_CTX][HEAD_DIM / 2];
static void rope_init(void) {
for (int p = 0; p < N_CTX; p++)
for (int d = 0; d < HEAD_DIM / 2; d++) {
float theta = (float)p / powf(ROPE_THETA, (float)(2 * d) / HEAD_DIM);
g_rope_cos[p][d] = cosf(theta);
g_rope_sin[p][d] = sinf(theta);
}
}
static void rope_apply(float *q, float *k, int pos) {
lal_rope_apply_simd(q, k, N_HEAD, N_KV_HEAD, HEAD_DIM, pos,
g_rope_cos[pos], g_rope_sin[pos]);
}
static void gqa_attn(float *out, const float *Q, const float *Kn, const float *Vn,
int layer, int pos) {
lal_gqa_attn_simd(out, Q, Kn, Vn, kv_k[layer], kv_v[layer], pos,
N_HEAD, N_KV_HEAD, HEAD_DIM, N_Q_PER_KV, KV_DIM, N_CTX);
}
/* === GPQ8 tensor file === */
typedef struct {
char key[128];
int ndim, shape[4];
int qtype; /* 0=F32, 1=Q8row, 3=Q8_0, 5=Q4_K, 6=TERNARY */
uint64_t data_len;
void *data;
int n_scale;
float *scale;
} GPQ8Tensor;
static GPQ8Tensor *g_gp_tensors;
static int g_gp_n;
static GPQ8Tensor *gp_find(const char *key) {
for (int i = 0; i < g_gp_n; i++)
if (strcmp(g_gp_tensors[i].key, key) == 0) return &g_gp_tensors[i];
fprintf(stderr, "[!] tensor not found: %s\n", key);
return NULL;
}
static void load_gpq8(const char *path) {
printf("[*] mmap-loading %s ...\n", path); fflush(stdout);
g_mmap_base = win_mmap_ro(path, &g_mmap_size);
/* warm pages: touch 1 byte per 64KB (fast, avoids inference stalls) */
{
volatile char sink = 0;
const char *base = (const char *)g_mmap_base;
for (size_t off = 0; off < g_mmap_size; off += 65536) sink += base[off];
printf("[*] mmap warmed (%.1f MB)\n", g_mmap_size / 1048576.0); fflush(stdout);
}
const unsigned char *p = (const unsigned char *)g_mmap_base;
if (memcmp(p, "GPQ8", 4) != 0) { fprintf(stderr, "[!] bad magic\n"); exit(1); }
p += 4;
g_gp_n = *(const int *)p; p += 4;
printf("[*] %d tensors (%.2f GB mmap'd)\n", g_gp_n, g_mmap_size / 1073741824.0);
fflush(stdout);
g_gp_tensors = calloc(g_gp_n, sizeof(GPQ8Tensor));
for (int i = 0; i < g_gp_n; i++) {
GPQ8Tensor *t = &g_gp_tensors[i];
int klen = *(const int *)p; p += 4;
memcpy(t->key, p, klen); t->key[klen] = 0; p += klen;
t->ndim = *(const int *)p; p += 4;
for (int d = 0; d < t->ndim; d++) { t->shape[d] = *(const int *)p; p += 4; }
t->qtype = *p; p += 1;
t->data_len = *(const uint64_t *)p; p += 8;
t->data = (void *)p; p += t->data_len;
t->n_scale = *(const int *)p; p += 4;
t->scale = (t->n_scale > 0) ? (float *)p : NULL;
if (t->n_scale > 0) p += (size_t)t->n_scale * 4;
}
printf("[*] all tensors mapped\n"); fflush(stdout);
}
static float *get_f32(const char *key) {
GPQ8Tensor *t = gp_find(key);
if (!t || t->qtype != 0) { fprintf(stderr, "[!] %s not F32\n", key); exit(1); }
return (float *)t->data;
}
static const uint8_t *get_packed(const char *key, int want_qtype) {
GPQ8Tensor *t = gp_find(key);
if (!t || t->qtype != want_qtype) {
fprintf(stderr, "[!] %s qtype=%d expected %d\n", key, t ? t->qtype : -1, want_qtype);
exit(1);
}
return (const uint8_t *)t->data;
}
/* === Layer struct: per-matrix qtype + packed pointer === */
typedef struct {
float *norm1_w, *norm2_w;
int tq, tk, tv, to, tgate, tup, tdown; /* per-matrix qtype (3/5/6) */
const uint8_t *wq, *wk, *wv, *wo, *wgate, *wup, *wdown;
} Layer;
static Layer g_layers[N_LAYER];
/* === Mixed-precision matmul dispatch === */
static void matmul_single(float *y, int qtype, const uint8_t *W,
const float *x, int in_dim, int out_dim) {
if (qtype == 3) {
parallel_matmul_q8_0_w(y, W, x, in_dim, out_dim);
return;
}
/* prepare x once (shared by Q4_K and TERNARY) */
static int8_t xq[XQ_MAX] __attribute__((aligned(32)));
static int16_t bsums[XQ_MAX / 32] __attribute__((aligned(32)));
static int8_t xq_arr[XQ_MAX] __attribute__((aligned(32)));
float xs = lal_q4k_prepare_x(x, in_dim, xq, bsums, xq_arr);
if (qtype == 5) {
parallel_matmul_q4_k_p(y, W, x, in_dim, out_dim, xq, bsums, xq_arr, xs);
} else if (qtype == 6) {
parallel_matmul_ternary(y, W, xq, xs, in_dim, out_dim);
} else {
fprintf(stderr, "[!] bad qtype %d\n", qtype); exit(1);
}
}
/* QKV: share one prepare across q/k/v when any is Q4_K/TERNARY */
static void matmul_qkv(Layer *L, const float *x) {
static int8_t xq[XQ_MAX] __attribute__((aligned(32)));
static int16_t bsums[XQ_MAX / 32] __attribute__((aligned(32)));
static int8_t xq_arr[XQ_MAX] __attribute__((aligned(32)));
float xs = 0;
if (L->tq == 5 || L->tq == 6 || L->tk == 5 || L->tv == 5)
xs = lal_q4k_prepare_x(x, N_EMBD, xq, bsums, xq_arr);
if (L->tq == 5)
parallel_matmul_q4_k_p(g_q, L->wq, x, N_EMBD, Q_DIM, xq, bsums, xq_arr, xs);
else if (L->tq == 6)
parallel_matmul_ternary(g_q, L->wq, xq, xs, N_EMBD, Q_DIM);
else
parallel_matmul_q8_0_w(g_q, L->wq, x, N_EMBD, Q_DIM);
if (L->tk == 5)
parallel_matmul_q4_k_p(g_k, L->wk, x, N_EMBD, KV_DIM, xq, bsums, xq_arr, xs);
else if (L->tk == 6)
parallel_matmul_ternary(g_k, L->wk, xq, xs, N_EMBD, KV_DIM);
else
parallel_matmul_q8_0_w(g_k, L->wk, x, N_EMBD, KV_DIM);
if (L->tv == 5)
parallel_matmul_q4_k_p(g_v, L->wv, x, N_EMBD, KV_DIM, xq, bsums, xq_arr, xs);
else if (L->tv == 6)
parallel_matmul_ternary(g_v, L->wv, xq, xs, N_EMBD, KV_DIM);
else
parallel_matmul_q8_0_w(g_v, L->wv, x, N_EMBD, KV_DIM);
}
/* MLP: gate/up (mixed) + SiLU + down (prepared from act) */
static void mlp_forward(Layer *L, const float *x, float *out) {
static float gate_buf[MLP_DIM], up_buf[MLP_DIM], act_buf[MLP_DIM];
static int8_t xq[XQ_MAX] __attribute__((aligned(32)));
static int16_t bsums[XQ_MAX / 32] __attribute__((aligned(32)));
static int8_t xq_arr[XQ_MAX] __attribute__((aligned(32)));
float xs = lal_q4k_prepare_x(x, N_EMBD, xq, bsums, xq_arr);
if (L->tgate == 5)
parallel_matmul_q4_k_p(gate_buf, L->wgate, x, N_EMBD, MLP_DIM, xq, bsums, xq_arr, xs);
else if (L->tgate == 6)
parallel_matmul_ternary(gate_buf, L->wgate, xq, xs, N_EMBD, MLP_DIM);
else
parallel_matmul_q8_0_w(gate_buf, L->wgate, x, N_EMBD, MLP_DIM);
if (L->tup == 5)
parallel_matmul_q4_k_p(up_buf, L->wup, x, N_EMBD, MLP_DIM, xq, bsums, xq_arr, xs);
else if (L->tup == 6)
parallel_matmul_ternary(up_buf, L->wup, xq, xs, N_EMBD, MLP_DIM);
else
parallel_matmul_q8_0_w(up_buf, L->wup, x, N_EMBD, MLP_DIM);
if (L->tdown == 5) {
/* fused SiLU(gate)*up + quantize act + bsums + rearrange for Q4_K down */
static int8_t d_xq[XQ_MAX] __attribute__((aligned(32)));
static int16_t d_bsums[XQ_MAX / 32] __attribute__((aligned(32)));
static int8_t d_xq_arr[XQ_MAX] __attribute__((aligned(32)));
float ds = lal_silu_mul_prepare_simd(act_buf, gate_buf, up_buf, MLP_DIM,
d_xq, d_bsums, d_xq_arr);
parallel_matmul_q4_k_p(out, L->wdown, act_buf, MLP_DIM, N_EMBD,
d_xq, d_bsums, d_xq_arr, ds);
} else if (L->tdown == 6) {
lal_silu_mul_simd(act_buf, gate_buf, up_buf, MLP_DIM);
static int8_t d_xq[XQ_MAX] __attribute__((aligned(32)));
static int16_t d_bsums[XQ_MAX / 32] __attribute__((aligned(32)));
static int8_t d_xq_arr[XQ_MAX] __attribute__((aligned(32)));
float ds = lal_q4k_prepare_x(act_buf, MLP_DIM, d_xq, d_bsums, d_xq_arr);
parallel_matmul_ternary(out, L->wdown, d_xq, ds, MLP_DIM, N_EMBD);
} else {
lal_silu_mul_simd(act_buf, gate_buf, up_buf, MLP_DIM);
parallel_matmul_q8_0_w(out, L->wdown, act_buf, MLP_DIM, N_EMBD);
}
}
static int forward(int tok, int pos) {
int dbg = getenv("LAL_DEBUG") ? atoi(getenv("LAL_DEBUG")) : 0;
if (tok < 0 || tok >= VOCAB_SIZE) tok = 0;
/* embedding lookup (Q8row -> f32) */
lal_dequant_row_f32(g_wte_q + (size_t)tok * N_EMBD, g_x, g_wte_s[tok], N_EMBD);
if (dbg) {
float s = 0; for (int i = 0; i < N_EMBD; i++) s += g_x[i] * g_x[i];
fprintf(stderr, "[dbg] emb |x|=%.4f x0=%f\n", sqrtf(s), g_x[0]);
}
for (int l = 0; l < N_LAYER; l++) {
Layer *L = &g_layers[l];
qwen_rms_norm(g_ln, g_x, L->norm1_w, N_EMBD);
matmul_qkv(L, g_ln);
if (dbg && l < 2) {
float s = 0; for (int i = 0; i < Q_DIM; i++) s += g_q[i] * g_q[i];
fprintf(stderr, "[dbg] L%d q|.|=%.4f q0=%f\n", l, sqrtf(s), g_q[0]);
}
rope_apply(g_q, g_k, pos);
gqa_attn(g_attn_out, g_q, g_k, g_v, l, pos);
matmul_single(g_proj, L->to, L->wo, g_attn_out, Q_DIM, N_EMBD);
lal_residual_add_simd(g_x, g_proj, N_EMBD);
if (dbg && l < 2) {
float s = 0; for (int i = 0; i < N_EMBD; i++) s += g_x[i] * g_x[i];
fprintf(stderr, "[dbg] L%d post-attn |x|=%.4f\n", l, sqrtf(s));
}
qwen_rms_norm(g_ln, g_x, L->norm2_w, N_EMBD);
mlp_forward(L, g_ln, g_mlp_out);
if (dbg && l < 2) {
float s = 0; for (int i = 0; i < N_EMBD; i++) s += g_mlp_out[i] * g_mlp_out[i];
fprintf(stderr, "[dbg] L%d mlp|.|=%.4f m0=%f\n", l, sqrtf(s), g_mlp_out[0]);
}
lal_residual_add_simd(g_x, g_mlp_out, N_EMBD);
}
qwen_rms_norm(g_ln, g_x, g_norm_f_w, N_EMBD);
if (dbg) {
float s = 0; for (int i = 0; i < N_EMBD; i++) s += g_ln[i] * g_ln[i];
fprintf(stderr, "[dbg] final |ln|=%.4f ln0=%f\n", sqrtf(s), g_ln[0]);
}
/* int8 LM head with abs-xq trick, parallel over vocab */
float scale_x = lal_quantize_x_int8(g_ln, g_xq_cache, N_EMBD);
static uint8_t abs_xq[N_EMBD] __attribute__((aligned(32)));
lal_compute_abs_xq(g_xq_cache, abs_xq, N_EMBD);
#pragma omp parallel num_threads(g_n_threads)
{
int tid = omp_get_thread_num();
int n = omp_get_num_threads();
int v_per = (VOCAB_SIZE + n - 1) / n;
int v_start = tid * v_per;
int v_end = v_start + v_per;
if (v_end > VOCAB_SIZE) v_end = VOCAB_SIZE;
if (v_start < VOCAB_SIZE)
lal_lm_head_int8_range_abs(g_logits, g_xq_cache, abs_xq, scale_x,
g_lm_head_q, g_lm_head_s,
v_start, v_end, N_EMBD);
}
/* sample */
if (dbg) {
int nan = 0;
for (int v = 0; v < VOCAB_SIZE; v++) {
float x = g_logits[v];
if (!(x == x) || x > 1e30f || x < -1e30f) nan++;
}
fprintf(stderr, "[dbg] logits nan/inf=%d L[0..7]=%.3f %.3f %.3f %.3f %.3f %.3f %.3f %.3f\n",
nan, g_logits[0], g_logits[1], g_logits[2], g_logits[3],
g_logits[4], g_logits[5], g_logits[6], g_logits[7]);
}
int next = lal_sample_token(g_logits, VOCAB_SIZE, g_temperature, g_top_k,
g_rep_penalty, g_recent, g_n_recent);
if (g_n_recent < 256) g_recent[g_n_recent++] = next;
else { memmove(g_recent, g_recent + 1, 255 * sizeof(int)); g_recent[255] = next; }
return next;
}
/* === Tokenizer: vocab hash + greedy longest-match over byte-level BPE space === */
typedef struct { char key[512]; int id; } TEntry;
#define TOK_HASH_BITS 18
#define TOK_HASH_SIZE (1 << TOK_HASH_BITS)
static TEntry g_htab[TOK_HASH_SIZE];
static char **g_vocab_str;
static int g_vocab_str_n;
static unsigned tok_hash(const char *s, int len) {
unsigned h = 2166136261u;
for (int i = 0; i < len; i++) { h ^= (unsigned char)s[i]; h *= 16777619u; }
return h & (TOK_HASH_SIZE - 1);
}
static void tins(const char *key, int id) {
unsigned h = tok_hash(key, (int)strlen(key));
while (g_htab[h].key[0]) h = (h + 1) & (TOK_HASH_SIZE - 1);
strncpy(g_htab[h].key, key, 511);
g_htab[h].key[511] = 0;
g_htab[h].id = id;
}
static int tok_find(const char *key) {
unsigned h = tok_hash(key, (int)strlen(key));
while (g_htab[h].key[0]) {
if (strcmp(g_htab[h].key, key) == 0) return g_htab[h].id;
h = (h + 1) & (TOK_HASH_SIZE - 1);
}
return -1;
}
static void load_tokenizer(const char *dir) {
/* vocab.tsv: "id<TAB>token" lines, generated from tokenizer.json
* (model.vocab + added_tokens merged; token escaped: \\ \t \n) */
char path[1024];
snprintf(path, sizeof(path), "%s/vocab.tsv", dir);
FILE *f = fopen(path, "rb");
if (!f) { fprintf(stderr, "[!] cannot open %s\n", path); exit(1); }
int mx = VOCAB_SIZE + 200;
g_vocab_str = calloc(mx, sizeof(char *));
char line[1024];
int cnt = 0;
while (fgets(line, sizeof line, f)) {
char *tab = strchr(line, '\t');
if (!tab) continue;
*tab = 0;
int id = atoi(line);
char *tok = tab + 1;
int len = (int)strlen(tok);
while (len && (tok[len - 1] == '\n' || tok[len - 1] == '\r')) tok[--len] = 0;
char real[512];
int r = 0;
for (int i = 0; i < len && r < 511; i++) {
if (tok[i] == '\\' && i + 1 < len) {
i++;
if (tok[i] == 't') real[r++] = '\t';
else if (tok[i] == 'n') real[r++] = '\n';
else if (tok[i] == 'r') real[r++] = '\r';
else real[r++] = tok[i];
} else real[r++] = tok[i];
}
real[r] = 0;
if (id >= 0 && id < mx) {
g_vocab_str[id] = strdup(real);
tins(real, id);
if (id + 1 > g_vocab_str_n) g_vocab_str_n = id + 1;
cnt++;
}
}
fclose(f);
printf("[*] tokenizer: %d tokens (max id %d)\n", cnt, g_vocab_str_n - 1);
}
/* convert raw utf-8 text to byte-level BPE "magic" string */
static int text_to_magic(const char *text, char *out, int cap) {
int n = 0;
for (const char *p = text; *p; p++) {
unsigned cp = lal_bpe_cp_for_byte((unsigned char)*p);
char tmp[5];
int m = lal_utf8_encode(cp, tmp);
for (int i = 0; i < m && n < cap - 1; i++) out[n++] = tmp[i];
}
out[n] = 0;
return n;
}
/* greedy longest-match encoding over the magic string */
static int *encode_text(const char *text, int *n_out) {
int cap = (int)strlen(text) * 4 + 8;
char *magic = malloc(cap);
int mlen = text_to_magic(text, magic, cap);
int *ids = malloc((mlen + 16) * sizeof(int));
int n = 0, pos = 0;
while (pos < mlen) {
int max_len = mlen - pos;
if (max_len > 48) max_len = 48;
int found = -1;
char tmp[64];
for (int len = max_len; len >= 1; len--) {
memcpy(tmp, magic + pos, len);
tmp[len] = 0;
found = tok_find(tmp);
if (found >= 0) { pos += len; break; }
}
if (found < 0) { /* single magic char should always match */
fprintf(stderr, "[!] encode stuck at %d\n", pos);
pos++;
continue;
}
ids[n++] = found;
}
free(magic);
*n_out = n;
return ids;
}
static void decode_token(int id, char *out, int maxlen) {
if (id < 0 || id >= g_vocab_str_n || !g_vocab_str[id]) { out[0] = 0; return; }
lal_decode_bpe_token(g_vocab_str[id], out, maxlen);
}
/* === Main === */
int main(int argc, char **argv) {
srand((unsigned)time(NULL));
const char *weights = "C:/models/minicpm_mixed.bin";
const char *tokdir = "C:/models/MiniCPM5-2B-cpu";
const char *prompt = NULL;
const char *prompt_file = NULL;
int n_gen = 48;
for (int i = 1; i < argc; i++) {
if (!strcmp(argv[i], "--weights") && i + 1 < argc) weights = argv[++i];
else if (!strcmp(argv[i], "--tokenizer") && i + 1 < argc) tokdir = argv[++i];
else if (!strcmp(argv[i], "--prompt") && i + 1 < argc) prompt = argv[++i];
else if (!strcmp(argv[i], "--prompt-file") && i + 1 < argc) prompt_file = argv[++i];
else if (!strcmp(argv[i], "--n") && i + 1 < argc) n_gen = atoi(argv[++i]);
else if (!strcmp(argv[i], "--threads") && i + 1 < argc) g_n_threads = atoi(argv[++i]);
else if (!strcmp(argv[i], "--temp") && i + 1 < argc) g_temperature = (float)atof(argv[++i]);
else if (!strcmp(argv[i], "--top-k") && i + 1 < argc) g_top_k = atoi(argv[++i]);
else if (!strcmp(argv[i], "--rep-penalty") && i + 1 < argc) g_rep_penalty = (float)atof(argv[++i]);
else { fprintf(stderr, "[?] unknown arg %s\n", argv[i]); }
}
static char prompt_buf[4096];
if (prompt_file) {
FILE *pf = fopen(prompt_file, "rb");
if (!pf) { fprintf(stderr, "[!] cannot open %s\n", prompt_file); return 1; }
size_t pn = fread(prompt_buf, 1, sizeof(prompt_buf) - 1, pf);
while (pn && (prompt_buf[pn - 1] == '\n' || prompt_buf[pn - 1] == '\r')) pn--;
prompt_buf[pn] = 0;
fclose(pf);
prompt = prompt_buf;
}
if (!prompt) prompt = "Hello";
printf("=== MiniCPM5-2B (LAL, mixed-precision: Q4_K body + Q8_0 edges + TERNARY gate/up) ===\n");
printf("[*] %d layers, %d hidden, %dQ/%dKV heads, %d head_dim, %d MLP, %d vocab\n",
N_LAYER, N_EMBD, N_HEAD, N_KV_HEAD, HEAD_DIM, MLP_DIM, VOCAB_SIZE);
printf("[*] threads=%d temp=%.2f top_k=%d\n", g_n_threads, g_temperature, g_top_k);
bit_lut_init();
load_gpq8(weights);
/* wire global tensors */
g_norm_f_w = get_f32("model.norm.weight");
{
GPQ8Tensor *t = gp_find("model.embed_tokens.weight");
if (!t || t->qtype != 1 || t->n_scale != VOCAB_SIZE) {
fprintf(stderr, "[!] embed_tokens Q8row mismatch\n"); exit(1);
}
g_wte_q = (int8_t *)t->data;
g_wte_s = t->scale;
}
{
GPQ8Tensor *t = gp_find("lm_head.weight");
if (!t || t->qtype != 1 || t->n_scale != VOCAB_SIZE) {
fprintf(stderr, "[!] lm_head Q8row mismatch\n"); exit(1);
}
g_lm_head_q = (int8_t *)t->data;
g_lm_head_s = t->scale;
}
/* wire layers (per-matrix mixed precision) */
char key[256];
int cnt_q8_0 = 0, cnt_q4k = 0, cnt_tern = 0;
for (int l = 0; l < N_LAYER; l++) {
Layer *L = &g_layers[l];
snprintf(key, sizeof(key), "model.layers.%d.input_layernorm.weight", l);
L->norm1_w = get_f32(key);
snprintf(key, sizeof(key), "model.layers.%d.post_attention_layernorm.weight", l);
L->norm2_w = get_f32(key);
struct { const char *name; int *t; const uint8_t **w; } mats[7] = {
{"self_attn.q_proj.weight", &L->tq, &L->wq},
{"self_attn.k_proj.weight", &L->tk, &L->wk},
{"self_attn.v_proj.weight", &L->tv, &L->wv},
{"self_attn.o_proj.weight", &L->to, &L->wo},
{"mlp.gate_proj.weight", &L->tgate, &L->wgate},
{"mlp.up_proj.weight", &L->tup, &L->wup},
{"mlp.down_proj.weight", &L->tdown, &L->wdown},
};
for (int m = 0; m < 7; m++) {
snprintf(key, sizeof(key), "model.layers.%d.%s", l, mats[m].name);
GPQ8Tensor *t = gp_find(key);
if (!t) exit(1);
*mats[m].t = t->qtype;
*mats[m].w = (const uint8_t *)t->data;
if (t->qtype == 3) cnt_q8_0++;
else if (t->qtype == 5) cnt_q4k++;
else if (t->qtype == 6) cnt_tern++;
}
}
printf("[*] layer matrices: %d x Q8_0 (8-bit edges), %d x Q4_K (4-bit), %d x TERNARY (3-value)\n",
cnt_q8_0, cnt_q4k, cnt_tern);
/* working buffers */
g_x = memalign(32, N_EMBD * sizeof(float));
g_ln = memalign(32, N_EMBD * sizeof(float));
g_q = memalign(32, Q_DIM * sizeof(float));
g_k = memalign(32, KV_DIM * sizeof(float));
g_v = memalign(32, KV_DIM * sizeof(float));
g_attn_out = memalign(32, Q_DIM * sizeof(float));
g_proj = memalign(32, N_EMBD * sizeof(float));
g_mlp_out = memalign(32, N_EMBD * sizeof(float));
g_logits = memalign(32, VOCAB_SIZE * sizeof(float));
g_xq_cache = memalign(32, N_EMBD);
/* KV cache: 42 x 2048 x 256 x 4B x 2 = 176 MB */
kv_k = malloc(N_LAYER * sizeof(float *));
kv_v = malloc(N_LAYER * sizeof(float *));
for (int l = 0; l < N_LAYER; l++) {
kv_k[l] = memalign(32, (size_t)N_CTX * KV_DIM * sizeof(float));
kv_v[l] = memalign(32, (size_t)N_CTX * KV_DIM * sizeof(float));
}
printf("[*] KV cache: %.0f MB\n", (double)N_LAYER * N_CTX * KV_DIM * 4 * 2 / 1048576);
rope_init();
load_tokenizer(tokdir);
/* special token ids (resolved from vocab) */
int tok_bos = tok_find("<s>");
int tok_im_start = tok_find("<|im_start|>");
int tok_im_end = tok_find("<|im_end|>");
printf("[*] special tokens: <s>=%d <|im_start|>=%d <|im_end|>=%d\n",
tok_bos, tok_im_start, tok_im_end);
/* build chat prompt (MiniCPM5 template, thinking disabled):
* <s><|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n<think>\n\n</think>\n\n */
int *pids = malloc((strlen(prompt) * 4 + 128) * sizeof(int));
int n_prompt = 0;
pids[n_prompt++] = tok_bos;
int nt;
int *t;
t = encode_text("<|im_start|>user\n", &nt);
for (int i = 0; i < nt; i++) pids[n_prompt++] = t[i];
free(t);
t = encode_text(prompt, &nt);
for (int i = 0; i < nt; i++) pids[n_prompt++] = t[i];
free(t);
/* debug: print prompt token ids + text */
{
int echo = getenv("ECHO_TOKENS") ? atoi(getenv("ECHO_TOKENS")) : 0;
if (echo) {
int base = 1; /* skip bos for display mapping */
fprintf(stderr, "[echo] prompt pieces:\n");
char buf[256];
for (int i = 1; i < n_prompt; i++) {
decode_token(pids[i], buf, (int)sizeof(buf));
fprintf(stderr, " %d -> id=%d text=[%s]\n", i, pids[i], buf);
}
(void)base;
}
}
t = encode_text("<|im_end|>\n", &nt);
for (int i = 0; i < nt; i++) pids[n_prompt++] = t[i];
free(t);
t = encode_text("<|im_start|>assistant\n<think>\n\n</think>\n\n", &nt);
for (int i = 0; i < nt; i++) pids[n_prompt++] = t[i];
free(t);
printf("[*] prompt: %d tokens (incl. chat template)\n", n_prompt);
printf("[*] generating %d tokens...\n\n", n_gen);
double t0 = now_sec();
int pos = 0, next = -1;
for (int i = 0; i < n_prompt; i++) {
next = forward(pids[i], pos);
pos++;
if (pos >= N_CTX) break;
}
double t_prefill = now_sec() - t0;
int gen_count = 0;
char out_buf[65536] = {0};
int opos = 0;
double t_gen0 = now_sec();
for (int g = 0; g < n_gen && pos < N_CTX; g++) {
char ts[256];
if (next >= 0 && next < g_vocab_str_n && g_vocab_str[next])
lal_decode_bpe_token(g_vocab_str[next], ts, (int)sizeof(ts));
else ts[0] = 0;
int slen = (int)strlen(ts);
if (opos + slen < (int)sizeof(out_buf) - 1) {
memcpy(out_buf + opos, ts, slen);
opos += slen;
}
if (next == tok_im_end || next == 1) break; /* EOS */
printf("%s", ts);
fflush(stdout);
next = forward(next, pos);
pos++;
gen_count++;
}
out_buf[opos] = 0;
double t_gen = now_sec() - t_gen0;
printf("\n\n[*] prefill: %d tokens in %.2fs (%.0f tok/s)\n",
n_prompt, t_prefill, n_prompt / (t_prefill + 1e-9));
printf("[*] decode: %d tokens in %.2fs (%.1f tok/s, %d threads)\n",
gen_count, t_gen, gen_count / (t_gen + 1e-9), g_n_threads);
printf("[*] output: %s\n", out_buf);
free(pids);
return 0;
}
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