系统信息

A100-80GB * 4

信息

• Docker
• CLI直接使用

任务

• 一个官方支持的命令
• 我自己的修改

复现

docker run -d \
--gpus '"device=4,5,6,7"' \
--shm-size 1g \
--name $model_name \
-p ${external_port}:80 -v $model_path:/data/CmwCoder \
-e WEIGHTS_CACHE_OVERRIDE="/data/CmwCoder" \
tgi:2.2.0 \
--weights-cache-override="/data/CmwCoder" \
--model-id "/data/CmwCoder" --num-shard $num_shard \
--max-input-length 14000 \
--max-total-tokens 16000 \
--max-batch-prefill-tokens 14000 \
--trust-remote-code \
--quantize gptq

预期行为

描述错误

当我使用Text-generation-inference 2.2.0对GPTQ量化模型DeepSeekCoderV2进行推理时，我遇到了错误 无法加载 gptq 权重以进行GPTQ -> Marlin重新打包，请确保模型已经量化。
config.json

{
  "_name_or_path": "/var/mntpkg/deepseek-coder-v2-instruct",
  "architectures": [
    "DeepseekV2ForCausalLM"
  ],
  "attention_bias": false,
  "attention_dropout": 0.0,
  "auto_map": {
    "AutoConfig": "configuration_deepseek.DeepseekV2Config",
    "AutoModel": "modeling_deepseek.DeepseekV2Model",
    "AutoModelForCausalLM": "modeling_deepseek.DeepseekV2ForCausalLM"
  },
  "aux_loss_alpha": 0.001,
  "bos_token_id": 100000,
  "eos_token_id": 100001,
  "ep_size": 1,
  "first_k_dense_replace": 1,
  "hidden_act": "silu",
  "hidden_size": 5120,
  "initializer_range": 0.02,
  "intermediate_size": 12288,
  "kv_lora_rank": 512,
  "max_position_embeddings": 163840,
  "model_type": "deepseek_v2",
  "moe_intermediate_size": 1536,
  "moe_layer_freq": 1,
  "n_group": 8,
  "n_routed_experts": 160,
  "n_shared_experts": 2,
  "norm_topk_prob": false,
  "num_attention_heads": 128,
  "num_experts_per_tok": 6,
  "num_hidden_layers": 60,
  "num_key_value_heads": 128,
  "pretraining_tp": 1,
  "q_lora_rank": 1536,
  "qk_nope_head_dim": 128,
  "qk_rope_head_dim": 64,
  "quantization_config": {
    "bits": 4,
    "checkpoint_format": "gptq",
    "damp_percent": 0.005,
    "desc_act": true,
    "dynamic_bits": null,
    "group_size": 128,
    "lm_head": false,
    "meta": {
      "quantizer": "gptqmodel:0.9.10-dev0"
    },
    "model_file_base_name": null,
    "model_name_or_path": null,
    "quant_method": "gptq",
    "static_groups": false,
    "sym": true,
    "true_sequential": true
  },
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "beta_fast": 32,
    "beta_slow": 1,
    "factor": 40,
    "mscale": 1.0,
    "mscale_all_dim": 1.0,
    "original_max_position_embeddings": 4096,
    "type": "yarn"
  },
  "rope_theta": 10000,
  "routed_scaling_factor": 16.0,
  "scoring_func": "softmax",
  "seq_aux": true,
  "tie_word_embeddings": false,
  "topk_group": 3,
  "topk_method": "group_limited_greedy",
  "torch_dtype": "bfloat16",
  "transformers_version": "4.43.3",
  "use_cache": true,
  "v_head_dim": 128,
  "vocab_size": 102400
}

quantize_config.json

{
  "bits": 4,
  "dynamic_bits": null,
  "group_size": 128,
  "desc_act": true,
  "static_groups": false,
  "sym": true,
  "lm_head": false,
  "damp_percent": 0.005,
  "true_sequential": true,
  "model_name_or_path": "deepseek-coder-v2-instruct-gptq",
  "model_file_base_name": "model",
  "quant_method": "gptq",
  "checkpoint_format": "gptq",
  "meta": {
    "quantizer": "gptqmodel:0.9.10-dev0"
 }

错误日志

2024-08-02 03:31:18.315 | INFO     | text_generation_server.utils.import_utils:<module>:75 - Detected system cuda
The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored.
The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored.
You are using a model of type deepseek_v2 to instantiate a model of type . This is not supported for all configurations of models and can yield errors.
[rank0]: Traceback (most recent call last):

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/layers/gptq/__init__.py", line 153, in get_weights
[rank0]:     qweight = weights.get_tensor(f"{prefix}.qweight")

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/utils/weights.py", line 212, in get_tensor
[rank0]:     filename, tensor_name = self.get_filename(tensor_name)

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/utils/weights.py", line 193, in get_filename
[rank0]:     raise RuntimeError(f"weight {tensor_name} does not exist")

[rank0]: RuntimeError: weight model.layers.59.self_attn.q_a_proj.qweight does not exist

[rank0]: During handling of the above exception, another exception occurred:

[rank0]: Traceback (most recent call last):

[rank0]:   File "/opt/conda/bin/text-generation-server", line 8, in <module>
[rank0]:     sys.exit(app())

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/cli.py", line 118, in serve
[rank0]:     server.serve(

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/server.py", line 297, in serve
[rank0]:     asyncio.run(

[rank0]:   File "/opt/conda/lib/python3.10/asyncio/runners.py", line 44, in run
[rank0]:     return loop.run_until_complete(main)

[rank0]:   File "/opt/conda/lib/python3.10/asyncio/base_events.py", line 649, in run_until_complete
[rank0]:     return future.result()

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/server.py", line 231, in serve_inner
[rank0]:     model = get_model(

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/models/__init__.py", line 490, in get_model
[rank0]:     return FlashCausalLM(

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/models/flash_causal_lm.py", line 898, in __init__
[rank0]:     model = model_class(prefix, config, weights)

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/models/custom_modeling/flash_deepseek_v2_modeling.py", line 764, in __init__
[rank0]:     self.model = DeepseekV2Model(

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/models/custom_modeling/flash_deepseek_v2_modeling.py", line 703, in __init__
[rank0]:     [

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/models/custom_modeling/flash_deepseek_v2_modeling.py", line 704, in <listcomp>
[rank0]:     DeepseekV2Layer(

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/models/custom_modeling/flash_deepseek_v2_modeling.py", line 626, in __init__
[rank0]:     self.self_attn = DeepseekV2Attention(

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/models/custom_modeling/flash_deepseek_v2_modeling.py", line 236, in __init__
[rank0]:     weight=weights.get_weights(f"{prefix}.q_a_proj"),

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/utils/weights.py", line 344, in get_weights
[rank0]:     return self.weights_loader.get_weights(self, prefix)

[rank0]:   File "/opt/conda/lib/python3.10/site-packages/text_generation_server/layers/gptq/__init__.py", line 155, in get_weights
[rank0]:     raise RuntimeError(

[rank0]: RuntimeError: Cannot load `gptq` weight for GPTQ -> Marlin repacking, make sure the model is already quantized
 rank=0
2024-08-02T04:51:40.980892Z ERROR text_generation_launcher: Shard 0 failed to start
2024-08-02T04:51:40.980912Z  INFO text_generation_launcher: Shutting down shards
2024-08-02T04:51:40.983834Z  INFO shard-manager: text_generation_launcher: Terminating shard rank=2
2024-08-02T04:51:40.984152Z  INFO shard-manager: text_generation_launcher: Waiting for shard to gracefully shutdown rank=2
2024-08-02T04:51:40.985398Z  INFO shard-manager: text_generation_launcher: Terminating shard rank=1
2024-08-02T04:51:40.985884Z  INFO shard-manager: text_generation_launcher: Waiting for shard to gracefully shutdown rank=1
2024-08-02T04:51:41.008435Z  INFO shard-manager: text_generation_launcher: Terminating shard rank=3
2024-08-02T04:51:41.008681Z  INFO shard-manager: text_generation_launcher: Waiting for shard to gracefully shutdown rank=3
2024-08-02T04:51:48.113698Z  INFO shard-manager: text_generation_launcher: shard terminated rank=3
2024-08-02T04:51:48.589678Z  INFO shard-manager: text_generation_launcher: shard terminated rank=2
2024-08-02T04:51:49.291857Z  INFO shard-manager: text_generation_launcher: shard terminated rank=1
Error: ShardCannotStart

附加上下文

我没有在 GPTQMode.from_quantized() 上遇到推理问题。