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Merge branch 'ggml-org:master' into ug/port-sweep-bench
2 parents 82f2cc1 + 9961d24 commit dc43ebd

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‎README.md‎

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -137,6 +137,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
137137
- [X] [Trillion-7B-preview](https://huggingface.co/trillionlabs/Trillion-7B-preview)
138138
- [x] [Ling models](https://huggingface.co/collections/inclusionAI/ling-67c51c85b34a7ea0aba94c32)
139139
- [x] [LFM2 models](https://huggingface.co/collections/LiquidAI/lfm2-686d721927015b2ad73eaa38)
140+
- [x] [Hunyuan models](https://huggingface.co/collections/tencent/hunyuan-dense-model-6890632cda26b19119c9c5e7)
140141

141142
#### Multimodal
142143

‎ci/run.sh‎

Lines changed: 10 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -386,10 +386,10 @@ function gg_run_open_llama_7b_v2 {
386386

387387
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
388388

389-
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
390-
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
391-
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
392-
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
389+
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 -fa off ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
390+
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 -fa on ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
391+
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa off ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
392+
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa on ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
393393

394394
function check_ppl {
395395
qnt="$1"
@@ -520,8 +520,8 @@ function gg_run_pythia_1_4b {
520520

521521
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
522522

523-
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
524-
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
523+
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa off ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
524+
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa on ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
525525

526526
function check_ppl {
527527
qnt="$1"
@@ -651,10 +651,10 @@ function gg_run_pythia_2_8b {
651651

652652
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
653653

654-
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
655-
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
656-
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
657-
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
654+
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 -fa off ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
655+
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 -fa on ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
656+
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa off ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
657+
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa on ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
658658

659659
function check_ppl {
660660
qnt="$1"

‎common/arg.cpp‎

Lines changed: 36 additions & 26 deletions
Original file line numberDiff line numberDiff line change
@@ -1106,7 +1106,7 @@ static void common_params_print_completion(common_params_context & ctx_arg) {
11061106
printf("\"\n\n");
11071107

11081108
printf(" case \"$prev\" in\n");
1109-
printf(" --model)\n");
1109+
printf(" --model|-m)\n");
11101110
printf(" COMPREPLY=( $(compgen -f -X '!*.gguf' -- \"$cur\") $(compgen -d -- \"$cur\") )\n");
11111111
printf(" return 0\n");
11121112
printf(" ;;\n");
@@ -1545,10 +1545,18 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
15451545
}
15461546
).set_examples({LLAMA_EXAMPLE_IMATRIX, LLAMA_EXAMPLE_PERPLEXITY, LLAMA_EXAMPLE_RETRIEVAL}));
15471547
add_opt(common_arg(
1548-
{"-fa", "--flash-attn"},
1549-
string_format("enable Flash Attention (default: %s)", params.flash_attn ? "enabled" : "disabled"),
1550-
[](common_params & params) {
1551-
params.flash_attn = true;
1548+
{"-fa", "--flash-attn"}, "FA",
1549+
string_format("set Flash Attention use ('on', 'off', or 'auto', default: '%s')", llama_flash_attn_type_name(params.flash_attn_type)),
1550+
[](common_params & params, const std::string & value) {
1551+
if (value == "on" || value == "enabled") {
1552+
params.flash_attn_type = LLAMA_FLASH_ATTN_TYPE_ENABLED;
1553+
} else if (value == "off" || value == "disabled") {
1554+
params.flash_attn_type = LLAMA_FLASH_ATTN_TYPE_DISABLED;
1555+
} else if (value == "auto") {
1556+
params.flash_attn_type = LLAMA_FLASH_ATTN_TYPE_AUTO;
1557+
} else {
1558+
throw std::runtime_error(string_format("error: unkown value for --flash-attn: '%s'\n", value.c_str()));
1559+
}
15521560
}
15531561
).set_env("LLAMA_ARG_FLASH_ATTN"));
15541562
add_opt(common_arg(
@@ -2555,15 +2563,15 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
25552563
{"--lora"}, "FNAME",
25562564
"path to LoRA adapter (can be repeated to use multiple adapters)",
25572565
[](common_params & params, const std::string & value) {
2558-
params.lora_adapters.push_back({ std::string(value), 1.0, nullptr });
2566+
params.lora_adapters.push_back({ std::string(value), 1.0, "", "", nullptr });
25592567
}
25602568
// we define this arg on both COMMON and EXPORT_LORA, so when showing help message of export-lora, it will be categorized as "example-specific" arg
25612569
).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_EXPORT_LORA}));
25622570
add_opt(common_arg(
25632571
{"--lora-scaled"}, "FNAME", "SCALE",
25642572
"path to LoRA adapter with user defined scaling (can be repeated to use multiple adapters)",
25652573
[](common_params & params, const std::string & fname, const std::string & scale) {
2566-
params.lora_adapters.push_back({ fname, std::stof(scale), nullptr });
2574+
params.lora_adapters.push_back({ fname, std::stof(scale), "", "", nullptr });
25672575
}
25682576
// we define this arg on both COMMON and EXPORT_LORA, so when showing help message of export-lora, it will be categorized as "example-specific" arg
25692577
).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_EXPORT_LORA}));
@@ -2954,20 +2962,20 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
29542962
params.endpoint_metrics = true;
29552963
}
29562964
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_ENDPOINT_METRICS"));
2957-
add_opt(common_arg(
2958-
{"--slots"},
2959-
string_format("enable slots monitoring endpoint (default: %s)", params.endpoint_slots ? "enabled" : "disabled"),
2960-
[](common_params & params) {
2961-
params.endpoint_slots = true;
2962-
}
2963-
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_ENDPOINT_SLOTS"));
29642965
add_opt(common_arg(
29652966
{"--props"},
29662967
string_format("enable changing global properties via POST /props (default: %s)", params.endpoint_props ? "enabled" : "disabled"),
29672968
[](common_params & params) {
29682969
params.endpoint_props = true;
29692970
}
29702971
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_ENDPOINT_PROPS"));
2972+
add_opt(common_arg(
2973+
{"--slots"},
2974+
string_format("enable slots monitoring endpoint (default: %s)", params.endpoint_slots ? "enabled" : "disabled"),
2975+
[](common_params & params) {
2976+
params.endpoint_slots = true;
2977+
}
2978+
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_ENDPOINT_SLOTS"));
29712979
add_opt(common_arg(
29722980
{"--no-slots"},
29732981
"disables slots monitoring endpoint",
@@ -3459,8 +3467,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
34593467
params.model.hf_repo = "ggml-org/Qwen2.5-Coder-1.5B-Q8_0-GGUF";
34603468
params.model.hf_file = "qwen2.5-coder-1.5b-q8_0.gguf";
34613469
params.port = 8012;
3462-
params.n_gpu_layers = 99;
3463-
params.flash_attn = true;
34643470
params.n_ubatch = 1024;
34653471
params.n_batch = 1024;
34663472
params.n_ctx = 0;
@@ -3475,8 +3481,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
34753481
params.model.hf_repo = "ggml-org/Qwen2.5-Coder-3B-Q8_0-GGUF";
34763482
params.model.hf_file = "qwen2.5-coder-3b-q8_0.gguf";
34773483
params.port = 8012;
3478-
params.n_gpu_layers = 99;
3479-
params.flash_attn = true;
34803484
params.n_ubatch = 1024;
34813485
params.n_batch = 1024;
34823486
params.n_ctx = 0;
@@ -3491,8 +3495,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
34913495
params.model.hf_repo = "ggml-org/Qwen2.5-Coder-7B-Q8_0-GGUF";
34923496
params.model.hf_file = "qwen2.5-coder-7b-q8_0.gguf";
34933497
params.port = 8012;
3494-
params.n_gpu_layers = 99;
3495-
params.flash_attn = true;
34963498
params.n_ubatch = 1024;
34973499
params.n_batch = 1024;
34983500
params.n_ctx = 0;
@@ -3508,10 +3510,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
35083510
params.model.hf_file = "qwen2.5-coder-7b-q8_0.gguf";
35093511
params.speculative.model.hf_repo = "ggml-org/Qwen2.5-Coder-0.5B-Q8_0-GGUF";
35103512
params.speculative.model.hf_file = "qwen2.5-coder-0.5b-q8_0.gguf";
3511-
params.speculative.n_gpu_layers = 99;
35123513
params.port = 8012;
3513-
params.n_gpu_layers = 99;
3514-
params.flash_attn = true;
35153514
params.n_ubatch = 1024;
35163515
params.n_batch = 1024;
35173516
params.n_ctx = 0;
@@ -3527,10 +3526,21 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
35273526
params.model.hf_file = "qwen2.5-coder-14b-q8_0.gguf";
35283527
params.speculative.model.hf_repo = "ggml-org/Qwen2.5-Coder-0.5B-Q8_0-GGUF";
35293528
params.speculative.model.hf_file = "qwen2.5-coder-0.5b-q8_0.gguf";
3530-
params.speculative.n_gpu_layers = 99;
35313529
params.port = 8012;
3532-
params.n_gpu_layers = 99;
3533-
params.flash_attn = true;
3530+
params.n_ubatch = 1024;
3531+
params.n_batch = 1024;
3532+
params.n_ctx = 0;
3533+
params.n_cache_reuse = 256;
3534+
}
3535+
).set_examples({LLAMA_EXAMPLE_SERVER}));
3536+
3537+
add_opt(common_arg(
3538+
{"--fim-qwen-30b-default"},
3539+
string_format("use default Qwen 3 Coder 30B A3B Instruct (note: can download weights from the internet)"),
3540+
[](common_params & params) {
3541+
params.model.hf_repo = "ggml-org/Qwen3-Coder-30B-A3B-Instruct-Q8_0-GGUF";
3542+
params.model.hf_file = "qwen3-coder-30b-a3b-instruct-q8_0.gguf";
3543+
params.port = 8012;
35343544
params.n_ubatch = 1024;
35353545
params.n_batch = 1024;
35363546
params.n_ctx = 0;

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