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aissatoubalde
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lab

Text Generation
Transformers
Safetensors
phi
custom_code
Inference Endpoints
text-generation-inference
Model card Files Community
aissatoubalde commited on
Commit
fe490e0
•
1 Parent(s): cc55646

Training in progress, epoch 0

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Files changed (5) hide show
  1. .ipynb_checkpoints/phi-2-custom-checkpoint.ipynb +0 -0
  2. adapter_config.json +6 -0
  3. fine-tuned-phi2.ipynb +9 -1002
  4. phi-2-custom.ipynb +0 -0
  5. training_args.bin +1 -1
.ipynb_checkpoints/phi-2-custom-checkpoint.ipynb CHANGED
The diff for this file is too large to render. See raw diff
 
adapter_config.json CHANGED
@@ -18,6 +18,12 @@
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  "r": 16,
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  "rank_pattern": {},
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  "revision": null,
 
 
 
 
 
 
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  "task_type": "CAUSAL_LM",
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  "use_rslora": false
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  }
 
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  "r": 16,
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  "rank_pattern": {},
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  "revision": null,
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+ "target_modules": [
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+ "fc2",
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+ "fc1",
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+ "v_proj",
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+ "q_proj"
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+ ],
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  "task_type": "CAUSAL_LM",
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  "use_rslora": false
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  }
fine-tuned-phi2.ipynb CHANGED
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 3,
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  "id": "75a61ec8-e440-42b0-8b4d-e3cb05841b71",
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  "metadata": {},
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- "outputs": [
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- {
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- "name": "stderr",
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- "output_type": "stream",
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- "text": [
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- "/usr/local/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
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- " from .autonotebook import tqdm as notebook_tqdm\n",
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- "2024-02-15 17:38:51,139\tINFO util.py:154 -- Missing packages: ['ipywidgets']. Run `pip install -U ipywidgets`, then restart the notebook server for rich notebook output.\n"
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- ]
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- }
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- ],
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  "source": [
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  "import torch\n",
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  "import numpy as np\n",
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 4,
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  "id": "7d29ba48-d4b0-4f24-8f88-560d9bed100c",
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  "metadata": {
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  "scrolled": true
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  },
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  "outputs": [
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- {
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- "name": "stderr",
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- "output_type": "stream",
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- "text": [
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- "config.json: 100%|██████████| 897/897 [00:00<00:00, 6.40MB/s]"
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- ]
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- },
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  {
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  "name": "stdout",
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  "output_type": "stream",
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  "text": [
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- "INFO 02-15 17:39:03 llm_engine.py:72] Initializing an LLM engine with config: model='aissatoubalde/lab', tokenizer='microsoft/phi-2', tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=2048, download_dir=None, load_format=auto, tensor_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, seed=0)\n"
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  ]
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  },
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  {
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  "name": "stderr",
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  "output_type": "stream",
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  "text": [
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- "\n",
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  "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
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  ]
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  },
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  "name": "stdout",
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  "text": [
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- "INFO 02-15 17:39:05 weight_utils.py:164] Using model weights format ['*.safetensors']\n"
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  ]
1262
  },
1263
  {
1264
  "ename": "KeyError",
1265
- "evalue": "'base_model.model.base_model.model.model.layers.0.self_attn.qkv_proj.lora_A.weight'",
1266
  "output_type": "error",
1267
  "traceback": [
1268
  "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
1269
  "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
1270
- "Cell \u001b[0;32mIn[4], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m base_model_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmicrosoft/phi-2\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 3\u001b[0m merged_peft_model_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124maissatoubalde/lab\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m----> 4\u001b[0m llm \u001b[38;5;241m=\u001b[39m \u001b[43mLLM\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmerged_peft_model_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtokenizer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbase_model_name\u001b[49m\u001b[43m)\u001b[49m\n",
1271
  "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/entrypoints/llm.py:109\u001b[0m, in \u001b[0;36mLLM.__init__\u001b[0;34m(self, model, tokenizer, tokenizer_mode, trust_remote_code, tensor_parallel_size, dtype, quantization, revision, tokenizer_revision, seed, gpu_memory_utilization, swap_space, enforce_eager, max_context_len_to_capture, disable_custom_all_reduce, **kwargs)\u001b[0m\n\u001b[1;32m 90\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdisable_log_stats\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 91\u001b[0m engine_args \u001b[38;5;241m=\u001b[39m EngineArgs(\n\u001b[1;32m 92\u001b[0m model\u001b[38;5;241m=\u001b[39mmodel,\n\u001b[1;32m 93\u001b[0m tokenizer\u001b[38;5;241m=\u001b[39mtokenizer,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 107\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m 108\u001b[0m )\n\u001b[0;32m--> 109\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mllm_engine \u001b[38;5;241m=\u001b[39m \u001b[43mLLMEngine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_engine_args\u001b[49m\u001b[43m(\u001b[49m\u001b[43mengine_args\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 110\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrequest_counter \u001b[38;5;241m=\u001b[39m Counter()\n",
1272
  "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/engine/llm_engine.py:356\u001b[0m, in \u001b[0;36mLLMEngine.from_engine_args\u001b[0;34m(cls, engine_args)\u001b[0m\n\u001b[1;32m 354\u001b[0m placement_group \u001b[38;5;241m=\u001b[39m initialize_cluster(parallel_config)\n\u001b[1;32m 355\u001b[0m \u001b[38;5;66;03m# Create the LLM engine.\u001b[39;00m\n\u001b[0;32m--> 356\u001b[0m engine \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mengine_configs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 357\u001b[0m \u001b[43m \u001b[49m\u001b[43mplacement_group\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 358\u001b[0m \u001b[43m \u001b[49m\u001b[43mlog_stats\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mengine_args\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdisable_log_stats\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 359\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m engine\n",
1273
  "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/engine/llm_engine.py:111\u001b[0m, in \u001b[0;36mLLMEngine.__init__\u001b[0;34m(self, model_config, cache_config, parallel_config, scheduler_config, lora_config, placement_group, log_stats)\u001b[0m\n\u001b[1;32m 109\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_init_workers_ray(placement_group)\n\u001b[1;32m 110\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 111\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_init_workers\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 113\u001b[0m \u001b[38;5;66;03m# Profile the memory usage and initialize the cache.\u001b[39;00m\n\u001b[1;32m 114\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_init_cache()\n",
@@ -1276,8 +283,8 @@
1276
  "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/worker/worker.py:92\u001b[0m, in \u001b[0;36mWorker.load_model\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 91\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mload_model\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m---> 92\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel_runner\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_model\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
1277
  "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/worker/model_runner.py:75\u001b[0m, in \u001b[0;36mModelRunner.load_model\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mload_model\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m---> 75\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel \u001b[38;5;241m=\u001b[39m \u001b[43mget_model\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel_config\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlora_config\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 77\u001b[0m vocab_size \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel\u001b[38;5;241m.\u001b[39mconfig\u001b[38;5;241m.\u001b[39mvocab_size\n\u001b[1;32m 79\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlora_config:\n",
1278
  "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/model_executor/model_loader.py:88\u001b[0m, in \u001b[0;36mget_model\u001b[0;34m(model_config, lora_config)\u001b[0m\n\u001b[1;32m 85\u001b[0m initialize_dummy_weights(model)\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 87\u001b[0m \u001b[38;5;66;03m# Load the weights from the cached or downloaded files.\u001b[39;00m\n\u001b[0;32m---> 88\u001b[0m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_weights\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel_config\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel_config\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdownload_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 89\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodel_config\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_format\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel_config\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 90\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m model\u001b[38;5;241m.\u001b[39meval()\n",
1279
- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/model_executor/models/phi.py:292\u001b[0m, in \u001b[0;36mPhiForCausalLM.load_weights\u001b[0;34m(self, model_name_or_path, cache_dir, load_format, revision)\u001b[0m\n\u001b[1;32m 290\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m name\u001b[38;5;241m.\u001b[39mendswith(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.bias\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;129;01mand\u001b[39;00m name \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m params_dict:\n\u001b[1;32m 291\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[0;32m--> 292\u001b[0m param \u001b[38;5;241m=\u001b[39m \u001b[43mparams_dict\u001b[49m\u001b[43m[\u001b[49m\u001b[43mname\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 293\u001b[0m weight_loader \u001b[38;5;241m=\u001b[39m param\u001b[38;5;241m.\u001b[39mweight_loader\n\u001b[1;32m 294\u001b[0m weight_loader(param, loaded_weight, shard_id)\n",
1280
- "\u001b[0;31mKeyError\u001b[0m: 'base_model.model.base_model.model.model.layers.0.self_attn.qkv_proj.lora_A.weight'"
1281
  ]
1282
  }
1283
  ],
 
225
  },
226
  {
227
  "cell_type": "code",
228
+ "execution_count": 5,
229
  "id": "75a61ec8-e440-42b0-8b4d-e3cb05841b71",
230
  "metadata": {},
231
+ "outputs": [],
 
 
 
 
 
 
 
 
 
 
232
  "source": [
233
  "import torch\n",
234
  "import numpy as np\n",
 
240
  },
241
  {
242
  "cell_type": "code",
243
+ "execution_count": 7,
244
  "id": "7d29ba48-d4b0-4f24-8f88-560d9bed100c",
245
  "metadata": {
246
  "scrolled": true
247
  },
248
  "outputs": [
 
 
 
 
 
 
 
249
  {
250
  "name": "stdout",
251
  "output_type": "stream",
252
  "text": [
253
+ "INFO 02-15 18:03:33 llm_engine.py:72] Initializing an LLM engine with config: model='aissatoubalde/lab', tokenizer='microsoft/phi-2', tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=2048, download_dir=None, load_format=auto, tensor_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, seed=0)\n"
254
  ]
255
  },
256
  {
257
  "name": "stderr",
258
  "output_type": "stream",
259
  "text": [
 
260
  "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
261
  ]
262
  },
 
264
  "name": "stdout",
265
  "output_type": "stream",
266
  "text": [
267
+ "INFO 02-15 18:03:33 weight_utils.py:164] Using model weights format ['*.safetensors']\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
268
  ]
269
  },
270
  {
271
  "ename": "KeyError",
272
+ "evalue": "'base_model.model.model.layers.0.mlp.fc1.lora_A.weight'",
273
  "output_type": "error",
274
  "traceback": [
275
  "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
276
  "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
277
+ "Cell \u001b[0;32mIn[7], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m base_model_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmicrosoft/phi-2\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 3\u001b[0m merged_peft_model_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124maissatoubalde/lab\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m----> 4\u001b[0m llm \u001b[38;5;241m=\u001b[39m \u001b[43mLLM\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmerged_peft_model_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtokenizer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbase_model_name\u001b[49m\u001b[43m)\u001b[49m\n",
278
  "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/entrypoints/llm.py:109\u001b[0m, in \u001b[0;36mLLM.__init__\u001b[0;34m(self, model, tokenizer, tokenizer_mode, trust_remote_code, tensor_parallel_size, dtype, quantization, revision, tokenizer_revision, seed, gpu_memory_utilization, swap_space, enforce_eager, max_context_len_to_capture, disable_custom_all_reduce, **kwargs)\u001b[0m\n\u001b[1;32m 90\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdisable_log_stats\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 91\u001b[0m engine_args \u001b[38;5;241m=\u001b[39m EngineArgs(\n\u001b[1;32m 92\u001b[0m model\u001b[38;5;241m=\u001b[39mmodel,\n\u001b[1;32m 93\u001b[0m tokenizer\u001b[38;5;241m=\u001b[39mtokenizer,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 107\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m 108\u001b[0m )\n\u001b[0;32m--> 109\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mllm_engine \u001b[38;5;241m=\u001b[39m \u001b[43mLLMEngine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_engine_args\u001b[49m\u001b[43m(\u001b[49m\u001b[43mengine_args\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 110\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrequest_counter \u001b[38;5;241m=\u001b[39m Counter()\n",
279
  "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/engine/llm_engine.py:356\u001b[0m, in \u001b[0;36mLLMEngine.from_engine_args\u001b[0;34m(cls, engine_args)\u001b[0m\n\u001b[1;32m 354\u001b[0m placement_group \u001b[38;5;241m=\u001b[39m initialize_cluster(parallel_config)\n\u001b[1;32m 355\u001b[0m \u001b[38;5;66;03m# Create the LLM engine.\u001b[39;00m\n\u001b[0;32m--> 356\u001b[0m engine \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mengine_configs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 357\u001b[0m \u001b[43m \u001b[49m\u001b[43mplacement_group\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 358\u001b[0m \u001b[43m \u001b[49m\u001b[43mlog_stats\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mengine_args\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdisable_log_stats\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 359\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m engine\n",
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  "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/engine/llm_engine.py:111\u001b[0m, in \u001b[0;36mLLMEngine.__init__\u001b[0;34m(self, model_config, cache_config, parallel_config, scheduler_config, lora_config, placement_group, log_stats)\u001b[0m\n\u001b[1;32m 109\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_init_workers_ray(placement_group)\n\u001b[1;32m 110\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 111\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_init_workers\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 113\u001b[0m \u001b[38;5;66;03m# Profile the memory usage and initialize the cache.\u001b[39;00m\n\u001b[1;32m 114\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_init_cache()\n",
 
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  "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/worker/worker.py:92\u001b[0m, in \u001b[0;36mWorker.load_model\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 91\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mload_model\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m---> 92\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel_runner\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_model\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
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  "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/worker/model_runner.py:75\u001b[0m, in \u001b[0;36mModelRunner.load_model\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mload_model\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m---> 75\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel \u001b[38;5;241m=\u001b[39m \u001b[43mget_model\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel_config\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlora_config\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 77\u001b[0m vocab_size \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel\u001b[38;5;241m.\u001b[39mconfig\u001b[38;5;241m.\u001b[39mvocab_size\n\u001b[1;32m 79\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlora_config:\n",
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  "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/model_executor/model_loader.py:88\u001b[0m, in \u001b[0;36mget_model\u001b[0;34m(model_config, lora_config)\u001b[0m\n\u001b[1;32m 85\u001b[0m initialize_dummy_weights(model)\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 87\u001b[0m \u001b[38;5;66;03m# Load the weights from the cached or downloaded files.\u001b[39;00m\n\u001b[0;32m---> 88\u001b[0m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_weights\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel_config\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel_config\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdownload_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 89\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodel_config\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_format\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel_config\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 90\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m model\u001b[38;5;241m.\u001b[39meval()\n",
286
+ "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/vllm/model_executor/models/phi.py:302\u001b[0m, in \u001b[0;36mPhiForCausalLM.load_weights\u001b[0;34m(self, model_name_or_path, cache_dir, load_format, revision)\u001b[0m\n\u001b[1;32m 299\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[1;32m 300\u001b[0m \u001b[38;5;66;03m# pylint: disable=E1136\u001b[39;00m\n\u001b[0;32m--> 302\u001b[0m param \u001b[38;5;241m=\u001b[39m \u001b[43mparams_dict\u001b[49m\u001b[43m[\u001b[49m\u001b[43mname\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 303\u001b[0m weight_loader \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(param, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mweight_loader\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 304\u001b[0m default_weight_loader)\n\u001b[1;32m 305\u001b[0m weight_loader(param, loaded_weight)\n",
287
+ "\u001b[0;31mKeyError\u001b[0m: 'base_model.model.model.layers.0.mlp.fc1.lora_A.weight'"
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  ]
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  }
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  ],
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