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Merge branch 'concedo_exp_b6060' into crokeso
2 parents 19536ca + c278a68 commit 857c599

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‎.devops/cann.Dockerfile‎

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# ==============================================================================
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# ARGUMENTS
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# ==============================================================================
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# Define the CANN base image for easier version updates later
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ARG CANN_BASE_IMAGE=quay.io/ascend/cann:8.1.rc1-910b-openeuler22.03-py3.10
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# ==============================================================================
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# BUILD STAGE
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# Compile all binary files and libraries
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# ==============================================================================
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FROM ${CANN_BASE_IMAGE} AS build
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# Define the Ascend chip model for compilation. Default is Ascend910B3
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ARG ASCEND_SOC_TYPE=Ascend910B3
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# -- Install build dependencies --
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RUN yum install -y gcc g++ cmake make git libcurl-devel python3 python3-pip && \
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yum clean all && \
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rm -rf /var/cache/yum
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# -- Set the working directory --
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WORKDIR /app
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# -- Copy project files --
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COPY . .
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# -- Set CANN environment variables (required for compilation) --
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# Using ENV instead of `source` allows environment variables to persist across the entire image layer
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ENV ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/latest
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ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${LD_LIBRARY_PATH}
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ENV PATH=${ASCEND_TOOLKIT_HOME}/bin:${PATH}
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ENV ASCEND_OPP_PATH=${ASCEND_TOOLKIT_HOME}/opp
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ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/runtime/lib64/stub:$LD_LIBRARY_PATH
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# ... You can add other environment variables from the original file as needed ...
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# For brevity, only core variables are listed here. You can paste the original ENV list here.
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# -- Build llama.cpp --
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# Use the passed ASCEND_SOC_TYPE argument and add general build options
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RUN source /usr/local/Ascend/ascend-toolkit/set_env.sh --force \
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&& \
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cmake -B build \
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-DGGML_CANN=ON \
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-DCMAKE_BUILD_TYPE=Release \
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-DSOC_TYPE=${ASCEND_SOC_TYPE} \
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. && \
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cmake --build build --config Release -j$(nproc)
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# -- Organize build artifacts for copying in later stages --
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# Create a lib directory to store all .so files
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RUN mkdir -p /app/lib && \
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find build -name "*.so" -exec cp {} /app/lib \;
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# Create a full directory to store all executables and Python scripts
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RUN mkdir -p /app/full && \
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cp build/bin/* /app/full/ && \
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cp *.py /app/full/ && \
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cp -r gguf-py /app/full/ && \
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cp -r requirements /app/full/ && \
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cp requirements.txt /app/full/
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# If you have a tools.sh script, make sure it is copied here
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# cp .devops/tools.sh /app/full/tools.sh
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# ==============================================================================
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# BASE STAGE
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# Create a minimal base image with CANN runtime and common libraries
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# ==============================================================================
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FROM ${CANN_BASE_IMAGE} AS base
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# -- Install runtime dependencies --
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RUN yum install -y libgomp curl && \
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yum clean all && \
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rm -rf /var/cache/yum
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# -- Set CANN environment variables (required for runtime) --
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ENV ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/latest
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ENV LD_LIBRARY_PATH=/app:${ASCEND_TOOLKIT_HOME}/lib64:${LD_LIBRARY_PATH}
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ENV PATH=${ASCEND_TOOLKIT_HOME}/bin:${PATH}
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ENV ASCEND_OPP_PATH=${ASCEND_TOOLKIT_HOME}/opp
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# ... You can add other environment variables from the original file as needed ...
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WORKDIR /app
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# Copy compiled .so files from the build stage
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COPY --from=build /app/lib/ /app
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# ==============================================================================
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# FINAL STAGES (TARGETS)
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# ==============================================================================
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### Target: full
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# Complete image with all tools, Python bindings, and dependencies
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# ==============================================================================
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FROM base AS full
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COPY --from=build /app/full /app
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# Install Python dependencies
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RUN yum install -y git python3 python3-pip && \
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pip3 install --no-cache-dir --upgrade pip setuptools wheel && \
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pip3 install --no-cache-dir -r requirements.txt && \
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yum clean all && \
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rm -rf /var/cache/yum
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# You need to provide a tools.sh script as the entrypoint
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ENTRYPOINT ["/app/tools.sh"]
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# If there is no tools.sh, you can set the default to start the server
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# ENTRYPOINT ["/app/llama-server"]
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### Target: light
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# Lightweight image containing only llama-cli
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# ==============================================================================
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FROM base AS light
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COPY --from=build /app/full/llama-cli /app
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ENTRYPOINT [ "/app/llama-cli" ]
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### Target: server
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# Dedicated server image containing only llama-server
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# ==============================================================================
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FROM base AS server
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ENV LLAMA_ARG_HOST=0.0.0.0
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COPY --from=build /app/full/llama-server /app
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HEALTHCHECK --interval=5m CMD [ "curl", "-f", "http://localhost:8080/health" ]
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ENTRYPOINT [ "/app/llama-server" ]

‎common/arg.cpp‎

Lines changed: 51 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -980,6 +980,10 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
980980
for (auto & seq_breaker : params.sampling.dry_sequence_breakers) {
981981
string_process_escapes(seq_breaker);
982982
}
983+
for (auto & pair : params.speculative.replacements) {
984+
string_process_escapes(pair.first);
985+
string_process_escapes(pair.second);
986+
}
983987
}
984988

985989
if (!params.kv_overrides.empty()) {
@@ -2094,6 +2098,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
20942098
params.no_kv_offload = true;
20952099
}
20962100
).set_env("LLAMA_ARG_NO_KV_OFFLOAD"));
2101+
add_opt(common_arg(
2102+
{"-nr", "--no-repack"},
2103+
"disable weight repacking",
2104+
[](common_params & params) {
2105+
params.no_extra_bufts = true;
2106+
}
2107+
).set_env("LLAMA_ARG_NO_REPACK"));
20972108
add_opt(common_arg(
20982109
{"-ctk", "--cache-type-k"}, "TYPE",
20992110
string_format(
@@ -2372,6 +2383,15 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
23722383
}
23732384
}
23742385
));
2386+
add_opt(common_arg(
2387+
{"--cpu-moe"},
2388+
"use CPU for Mixture of Experts (MoE) weights",
2389+
[](common_params & params) {
2390+
params.tensor_buft_overrides.push_back({"\\.ffn_up_exps\\.weight$", ggml_backend_cpu_buffer_type()});
2391+
params.tensor_buft_overrides.push_back({"\\.ffn_down_exps\\.weight$", ggml_backend_cpu_buffer_type()});
2392+
params.tensor_buft_overrides.push_back({"\\.ffn_gate_exps\\.weight$", ggml_backend_cpu_buffer_type()});
2393+
}
2394+
).set_env("LLAMA_ARG_CPU_MOE"));
23752395
add_opt(common_arg(
23762396
{"-ngl", "--gpu-layers", "--n-gpu-layers"}, "N",
23772397
"number of layers to store in VRAM",
@@ -3252,6 +3272,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
32523272
params.speculative.model.path = value;
32533273
}
32543274
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_MODEL_DRAFT"));
3275+
add_opt(common_arg(
3276+
{"--spec-replace"}, "TARGET", "DRAFT",
3277+
"translate the string in TARGET into DRAFT if the draft model and main model are not compatible",
3278+
[](common_params & params, const std::string & tgt, const std::string & dft) {
3279+
params.speculative.replacements.push_back({ tgt, dft });
3280+
}
3281+
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}));
32553282
add_opt(common_arg(
32563283
{"-ctkd", "--cache-type-k-draft"}, "TYPE",
32573284
string_format(
@@ -3441,34 +3468,51 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
34413468
}
34423469
).set_examples({LLAMA_EXAMPLE_SERVER}));
34433470

3444-
// diffusion parameters
34453471
add_opt(common_arg(
34463472
{ "--diffusion-steps" }, "N",
34473473
string_format("number of diffusion steps (default: %d)", params.diffusion.steps),
34483474
[](common_params & params, int value) { params.diffusion.steps = value; }
34493475
).set_examples({ LLAMA_EXAMPLE_DIFFUSION }));
3476+
add_opt(common_arg(
3477+
{ "--diffusion-visual" },
3478+
string_format("enable visual diffusion mode (show progressive generation) (default: %s)",
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params.diffusion.visual_mode ? "true" : "false"),
3480+
[](common_params & params) { params.diffusion.visual_mode = true; }
3481+
).set_examples({ LLAMA_EXAMPLE_DIFFUSION }));
3482+
34503483
add_opt(common_arg(
34513484
{ "--diffusion-eps" }, "F",
34523485
string_format("epsilon for timesteps (default: %.6f)", (double) params.diffusion.eps),
34533486
[](common_params & params, const std::string & value) { params.diffusion.eps = std::stof(value); }
34543487
).set_examples({ LLAMA_EXAMPLE_DIFFUSION }));
34553488
add_opt(common_arg(
34563489
{ "--diffusion-algorithm" }, "N",
3457-
string_format("diffusion algorithm: 0=ORIGIN, 1=MASKGIT_PLUS, 2=TOPK_MARGIN, 3=ENTROPY (default: %d)",
3490+
string_format("diffusion algorithm: 0=ORIGIN, 1=ENTROPY_BASED, 2=MARGIN_BASED, 3=RANDOM, 4=LOW_CONFIDENCE (default: %d)",
34583491
params.diffusion.algorithm),
34593492
[](common_params & params, int value) { params.diffusion.algorithm = value; }
34603493
).set_examples({ LLAMA_EXAMPLE_DIFFUSION }));
34613494
add_opt(common_arg(
34623495
{ "--diffusion-alg-temp" }, "F",
3463-
string_format("algorithm temperature (default: %.3f)", (double) params.diffusion.alg_temp),
3496+
string_format("dream algorithm temperature (default: %.3f)", (double) params.diffusion.alg_temp),
34643497
[](common_params & params, const std::string & value) { params.diffusion.alg_temp = std::stof(value); }
34653498
).set_examples({ LLAMA_EXAMPLE_DIFFUSION }));
3499+
34663500
add_opt(common_arg(
3467-
{ "--diffusion-visual" },
3468-
string_format("enable visual diffusion mode (show progressive generation) (default: %s)",
3469-
params.diffusion.visual_mode ? "true" : "false"),
3470-
[](common_params & params) { params.diffusion.visual_mode = true; }
3501+
{ "--diffusion-block-length" }, "N",
3502+
string_format("llada block length for generation (default: %d)", params.diffusion.block_length),
3503+
[](common_params & params, int value) { params.diffusion.block_length = value; }
3504+
).set_examples({ LLAMA_EXAMPLE_DIFFUSION }));
3505+
add_opt(common_arg(
3506+
{ "--diffusion-cfg-scale" }, "F",
3507+
string_format("llada classifier-free guidance scale (default: %.3f)", (double) params.diffusion.cfg_scale),
3508+
[](common_params & params, const std::string & value) { params.diffusion.cfg_scale = std::stof(value); }
34713509
).set_examples({ LLAMA_EXAMPLE_DIFFUSION }));
3510+
add_opt(common_arg(
3511+
{ "--diffusion-add-gumbel-noise" }, "F",
3512+
string_format("add gumbel noise to the logits if temp > 0.0 (default: %s)", params.diffusion.add_gumbel_noise ? "true" : "false"),
3513+
[](common_params & params, const std::string & value) { params.diffusion.add_gumbel_noise = std::stof(value); }
3514+
).set_examples({ LLAMA_EXAMPLE_DIFFUSION }));
3515+
34723516

34733517
return ctx_arg;
34743518
}

‎common/common.cpp‎

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1131,6 +1131,7 @@ struct llama_model_params common_model_params_to_llama(common_params & params) {
11311131
mparams.use_mlock = params.use_mlock;
11321132
mparams.check_tensors = params.check_tensors;
11331133
mparams.requested_n_ctx = params.n_ctx;
1134+
mparams.use_extra_bufts = !params.no_extra_bufts;
11341135

11351136
if (params.kv_overrides.empty()) {
11361137
mparams.kv_overrides = NULL;

‎common/common.h‎

Lines changed: 13 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -197,6 +197,7 @@ struct common_params_speculative {
197197
int32_t n_gpu_layers = -1; // number of layers to store in VRAM for the draft model (-1 - use default)
198198
float p_split = 0.1f; // speculative decoding split probability
199199
float p_min = 0.75f; // minimum speculative decoding probability (greedy)
200+
std::vector<std::pair<std::string, std::string>> replacements; // main to speculative model replacements
200201

201202
ggml_type cache_type_k = GGML_TYPE_F16; // KV cache data type for the K
202203
ggml_type cache_type_v = GGML_TYPE_F16; // KV cache data type for the V
@@ -216,11 +217,17 @@ struct common_params_vocoder {
216217
};
217218

218219
struct common_params_diffusion {
219-
int32_t steps = 64; // number of diffusion steps
220-
float eps = 1e-3f; // epsilon for timesteps
221-
int32_t algorithm = 0; // diffusion algorithm (0=ORIGIN, 1=MASKGIT_PLUS, 2=TOPK_MARGIN, 3=ENTROPY)
222-
float alg_temp = 0.0f; // algorithm temperature
223-
bool visual_mode = false; // show progressive diffusion on screen
220+
int32_t steps = 128;
221+
bool visual_mode = false;
222+
223+
float eps = 0; // epsilon for timesteps
224+
int32_t block_length = 0; // block length for generation
225+
226+
int32_t algorithm = 4; // default algorithm: low-confidence
227+
float alg_temp = 0.0f; // algorithm temperature
228+
229+
float cfg_scale = 0; // classifier-free guidance scale
230+
bool add_gumbel_noise = false; // add gumbel noise to the logits if temp > 0.0
224231
};
225232

226233
enum common_reasoning_format {
@@ -348,6 +355,7 @@ struct common_params {
348355
bool warmup = true; // warmup run
349356
bool check_tensors = false; // validate tensor data
350357
bool no_op_offload = false; // globally disable offload host tensor operations to device
358+
bool no_extra_bufts = false; // disable extra buffer types (used for weight repacking)
351359

352360
bool single_turn = false; // single turn chat conversation
353361

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