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merged 2 commits into from
Feb 13, 2025
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This PR updates the MUSA SDK version from rc3.1.0 to rc3.1.1 and removes the workaround introduced in #10042.

Testing Done

Tested deepseek-r1_7b_q4_k.gguf locally (MTT S80), everything functions as expected. Please see the logs below:

❯ ./llama-cli -m ~/models/deepseek-r1_7b_q4_k.gguf -ngl 999
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 MUSA devices:
  Device 0: MTT S80, compute capability 2.1, VMM: yes
build: 4693 (100d2401) with cc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 for x86_64-linux-gnu
main: llama backend init
main: load the model and apply lora adapter, if any
llama_model_load_from_file_impl: using device MUSA0 (MTT S80) - 16292 MiB free
llama_model_loader: loaded meta data with 26 key-value pairs and 339 tensors from /home/xiaodongye/models/deepseek-r1_7b_q4_0.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = qwen2
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = DeepSeek R1 Distill Qwen 7B
llama_model_loader: - kv   3:                           general.basename str              = DeepSeek-R1-Distill-Qwen
llama_model_loader: - kv   4:                         general.size_label str              = 7B
llama_model_loader: - kv   5:                          qwen2.block_count u32              = 28
llama_model_loader: - kv   6:                       qwen2.context_length u32              = 131072
llama_model_loader: - kv   7:                     qwen2.embedding_length u32              = 3584
llama_model_loader: - kv   8:                  qwen2.feed_forward_length u32              = 18944
llama_model_loader: - kv   9:                 qwen2.attention.head_count u32              = 28
llama_model_loader: - kv  10:              qwen2.attention.head_count_kv u32              = 4
llama_model_loader: - kv  11:                       qwen2.rope.freq_base f32              = 10000.000000
llama_model_loader: - kv  12:     qwen2.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  13:                          general.file_type u32              = 15
llama_model_loader: - kv  14:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  15:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  16:                      tokenizer.ggml.tokens arr[str,152064]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  17:                  tokenizer.ggml.token_type arr[i32,152064]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  18:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  19:                tokenizer.ggml.bos_token_id u32              = 151646
llama_model_loader: - kv  20:                tokenizer.ggml.eos_token_id u32              = 151643
llama_model_loader: - kv  21:            tokenizer.ggml.padding_token_id u32              = 151643
llama_model_loader: - kv  22:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  23:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  24:                    tokenizer.chat_template str              = {% if not add_generation_prompt is de...
llama_model_loader: - kv  25:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:  141 tensors
llama_model_loader: - type q4_K:  169 tensors
llama_model_loader: - type q6_K:   29 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_K - Medium
print_info: file size   = 4.36 GiB (4.91 BPW) 
load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
load: special tokens cache size = 22
load: token to piece cache size = 0.9310 MB
print_info: arch             = qwen2
print_info: vocab_only       = 0
print_info: n_ctx_train      = 131072
print_info: n_embd           = 3584
print_info: n_layer          = 28
print_info: n_head           = 28
print_info: n_head_kv        = 4
print_info: n_rot            = 128
print_info: n_swa            = 0
print_info: n_embd_head_k    = 128
print_info: n_embd_head_v    = 128
print_info: n_gqa            = 7
print_info: n_embd_k_gqa     = 512
print_info: n_embd_v_gqa     = 512
print_info: f_norm_eps       = 0.0e+00
print_info: f_norm_rms_eps   = 1.0e-06
print_info: f_clamp_kqv      = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale    = 0.0e+00
print_info: n_ff             = 18944
print_info: n_expert         = 0
print_info: n_expert_used    = 0
print_info: causal attn      = 1
print_info: pooling type     = 0
print_info: rope type        = 2
print_info: rope scaling     = linear
print_info: freq_base_train  = 10000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn  = 131072
print_info: rope_finetuned   = unknown
print_info: ssm_d_conv       = 0
print_info: ssm_d_inner      = 0
print_info: ssm_d_state      = 0
print_info: ssm_dt_rank      = 0
print_info: ssm_dt_b_c_rms   = 0
print_info: model type       = 7B
print_info: model params     = 7.62 B
print_info: general.name     = DeepSeek R1 Distill Qwen 7B
print_info: vocab type       = BPE
print_info: n_vocab          = 152064
print_info: n_merges         = 151387
print_info: BOS token        = 151646 '<|begin▁of▁sentence|>'
print_info: EOS token        = 151643 '<|end▁of▁sentence|>'
print_info: EOT token        = 151643 '<|end▁of▁sentence|>'
print_info: PAD token        = 151643 '<|end▁of▁sentence|>'
print_info: LF token         = 198 'Ċ'
print_info: FIM PRE token    = 151659 '<|fim_prefix|>'
print_info: FIM SUF token    = 151661 '<|fim_suffix|>'
print_info: FIM MID token    = 151660 '<|fim_middle|>'
print_info: FIM PAD token    = 151662 '<|fim_pad|>'
print_info: FIM REP token    = 151663 '<|repo_name|>'
print_info: FIM SEP token    = 151664 '<|file_sep|>'
print_info: EOG token        = 151643 '<|end▁of▁sentence|>'
print_info: EOG token        = 151662 '<|fim_pad|>'
print_info: EOG token        = 151663 '<|repo_name|>'
print_info: EOG token        = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 28 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 29/29 layers to GPU
load_tensors:        MUSA0 model buffer size =  4168.09 MiB
load_tensors:   CPU_Mapped model buffer size =   292.36 MiB
..................................................................................
llama_init_from_model: n_seq_max     = 1
llama_init_from_model: n_ctx         = 4096
llama_init_from_model: n_ctx_per_seq = 4096
llama_init_from_model: n_batch       = 2048
llama_init_from_model: n_ubatch      = 512
llama_init_from_model: flash_attn    = 0
llama_init_from_model: freq_base     = 10000.0
llama_init_from_model: freq_scale    = 1
llama_init_from_model: n_ctx_per_seq (4096) < n_ctx_train (131072) -- the full capacity of the model will not be utilized
llama_kv_cache_init: kv_size = 4096, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 28, can_shift = 1
llama_kv_cache_init:      MUSA0 KV buffer size =   224.00 MiB
llama_init_from_model: KV self size  =  224.00 MiB, K (f16):  112.00 MiB, V (f16):  112.00 MiB
llama_init_from_model:  MUSA_Host  output buffer size =     0.58 MiB
llama_init_from_model:      MUSA0 compute buffer size =   304.00 MiB
llama_init_from_model:  MUSA_Host compute buffer size =    15.01 MiB
llama_init_from_model: graph nodes  = 986
llama_init_from_model: graph splits = 2
common_init_from_params: setting dry_penalty_last_n to ctx_size = 4096
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
main: llama threadpool init, n_threads = 6
main: chat template is available, enabling conversation mode (disable it with -no-cnv)
main: chat template example:
You are a helpful assistant

<|User|>Hello<|Assistant|>Hi there<|end▁of▁sentence|><|User|>How are you?<|Assistant|>

system_info: n_threads = 6 (n_threads_batch = 6) / 12 | MUSA : USE_GRAPHS = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | LLAMAFILE = 1 | OPENMP = 1 | AARCH64_REPACK = 1 | 

main: interactive mode on.
sampler seed: 1860307736
sampler params: 
        repeat_last_n = 64, repeat_penalty = 1.000, frequency_penalty = 0.000, presence_penalty = 0.000
        dry_multiplier = 0.000, dry_base = 1.750, dry_allowed_length = 2, dry_penalty_last_n = 4096
        top_k = 40, top_p = 0.950, min_p = 0.050, xtc_probability = 0.000, xtc_threshold = 0.100, typical_p = 1.000, temp = 0.800
        mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000
sampler chain: logits -> logit-bias -> penalties -> dry -> top-k -> typical -> top-p -> min-p -> xtc -> temp-ext -> dist 
generate: n_ctx = 4096, n_batch = 2048, n_predict = -1, n_keep = 1

== Running in interactive mode. ==
 - Press Ctrl+C to interject at any time.
 - Press Return to return control to the AI.
 - To return control without starting a new line, end your input with '/'.
 - If you want to submit another line, end your input with '\'.
 - Using default system message. To change it, set a different value via -p PROMPT or -f FILE argument.

You are a helpful assistant


> Hi, who are you?
<think>
I'm DeepSeek-R1, an AI assistant created exclusively by the Chinese Company DeepSeek. I specialize in helping you tackle complex STEM challenges through analytical thinking, especially tailoring solutions for scientists and engineers.
</think>

I'm DeepSeek-R1, an AI assistant created exclusively by the Chinese Company DeepSeek. I specialize in helping you tackle complex STEM challenges through analytical thinking, especially tailoring solutions for scientists and engineers.

@github-actions github-actions bot added documentation Improvements or additions to documentation Nvidia GPU Issues specific to Nvidia GPUs devops improvements to build systems and github actions ggml changes relating to the ggml tensor library for machine learning labels Feb 12, 2025
@yeahdongcn yeahdongcn marked this pull request as ready for review February 13, 2025 11:31
@yeahdongcn yeahdongcn requested a review from ngxson as a code owner February 13, 2025 11:31
@ngxson ngxson merged commit bd6e55b into ggml-org:master Feb 13, 2025
46 checks passed
orca-zhang pushed a commit to orca-zhang/llama.cpp that referenced this pull request Feb 26, 2025
* musa: Update MUSA SDK version to rc3.1.1

Signed-off-by: Xiaodong Ye <[email protected]>

* musa: Remove workaround in PR ggml-org#10042

Signed-off-by: Xiaodong Ye <[email protected]>

---------

Signed-off-by: Xiaodong Ye <[email protected]>
arthw pushed a commit to arthw/llama.cpp that referenced this pull request Feb 26, 2025
* musa: Update MUSA SDK version to rc3.1.1

Signed-off-by: Xiaodong Ye <[email protected]>

* musa: Remove workaround in PR ggml-org#10042

Signed-off-by: Xiaodong Ye <[email protected]>

---------

Signed-off-by: Xiaodong Ye <[email protected]>
mglambda pushed a commit to mglambda/llama.cpp that referenced this pull request Mar 8, 2025
* musa: Update MUSA SDK version to rc3.1.1

Signed-off-by: Xiaodong Ye <[email protected]>

* musa: Remove workaround in PR ggml-org#10042

Signed-off-by: Xiaodong Ye <[email protected]>

---------

Signed-off-by: Xiaodong Ye <[email protected]>
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