Hugging Face's logo

psychologyphd
/
CodeLlama-7b-Text-to-SQL-mps-finetuned

Text Generation
PEFT
Safetensors
English
llama
text-to-sql
code
lora
nlp
mps
conversational
Model card Files
xet
Community
psychologyphd commited on
Commit
4fa8b98
·
verified ·
1 Parent(s): b886819

Upload how_to_use.ipynb

Browse files
Files changed (1) hide show
  1. how_to_use.ipynb +212 -0
how_to_use.ipynb ADDED
@@ -0,0 +1,212 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "cells": [
3
+ {
4
+ "cell_type": "code",
5
+ "execution_count": 1,
6
+ "id": "95945cf4",
7
+ "metadata": {},
8
+ "outputs": [],
9
+ "source": [
10
+ "# Cell 1: 安装依赖 (如果还没装)\n",
11
+ "# !pip install -q transformers torch accelerate"
12
+ ]
13
+ },
14
+ {
15
+ "cell_type": "code",
16
+ "execution_count": 1,
17
+ "id": "063e56f2",
18
+ "metadata": {},
19
+ "outputs": [
20
+ {
21
+ "name": "stdout",
22
+ "output_type": "stream",
23
+ "text": [
24
+ "🚀 环境已重置，使用设备: mps\n",
25
+ "⏳ 正在加载模型 (MPS + Float16)...\n"
26
+ ]
27
+ },
28
+ {
29
+ "name": "stderr",
30
+ "output_type": "stream",
31
+ "text": [
32
+ "python(51576) MallocStackLogging: can't turn off malloc stack logging because it was not enabled.\n"
33
+ ]
34
+ },
35
+ {
36
+ "data": {
37
+ "application/vnd.jupyter.widget-view+json": {
38
+ "model_id": "4f71a457fb0f4f7dbcfd0f002224ffb8",
39
+ "version_major": 2,
40
+ "version_minor": 0
41
+ },
42
+ "text/plain": [
43
+ "Downloading shards: 0%| | 0/3 [00:00<?, ?it/s]"
44
+ ]
45
+ },
46
+ "metadata": {},
47
+ "output_type": "display_data"
48
+ },
49
+ {
50
+ "data": {
51
+ "application/vnd.jupyter.widget-view+json": {
52
+ "model_id": "59f84747f1744f7dbea42305928cc554",
53
+ "version_major": 2,
54
+ "version_minor": 0
55
+ },
56
+ "text/plain": [
57
+ "model-00001-of-00003.safetensors: 20%|## | 1.01G/4.94G [00:00<?, ?B/s]"
58
+ ]
59
+ },
60
+ "metadata": {},
61
+ "output_type": "display_data"
62
+ },
63
+ {
64
+ "ename": "KeyboardInterrupt",
65
+ "evalue": "",
66
+ "output_type": "error",
67
+ "traceback": [
68
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
69
+ "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
70
+ "Cell \u001b[0;32mIn[1], line 19\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m⏳ 正在加载模型 (MPS + Float16)...\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 18\u001b[0m \u001b[38;5;66;03m# 加载 Base Model\u001b[39;00m\n\u001b[0;32m---> 19\u001b[0m model \u001b[38;5;241m=\u001b[39m AutoModelForCausalLM\u001b[38;5;241m.\u001b[39mfrom_pretrained(\n\u001b[1;32m 20\u001b[0m model_id,\n\u001b[1;32m 21\u001b[0m device_map\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m: device}, \n\u001b[1;32m 22\u001b[0m torch_dtype\u001b[38;5;241m=\u001b[39mtorch\u001b[38;5;241m.\u001b[39mfloat16, \u001b[38;5;66;03m# 半精度，省显存\u001b[39;00m\n\u001b[1;32m 23\u001b[0m )\n\u001b[1;32m 26\u001b[0m model\u001b[38;5;241m.\u001b[39meval()\n\u001b[1;32m 28\u001b[0m \u001b[38;5;66;03m# 加载 Tokenizer\u001b[39;00m\n",
71
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/transformers/models/auto/auto_factory.py:564\u001b[0m, in \u001b[0;36m_BaseAutoModelClass.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m 562\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(config) \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys():\n\u001b[1;32m 563\u001b[0m model_class \u001b[38;5;241m=\u001b[39m _get_model_class(config, \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping)\n\u001b[0;32m--> 564\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m model_class\u001b[38;5;241m.\u001b[39mfrom_pretrained(\n\u001b[1;32m 565\u001b[0m pretrained_model_name_or_path, \u001b[38;5;241m*\u001b[39mmodel_args, config\u001b[38;5;241m=\u001b[39mconfig, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mhub_kwargs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs\n\u001b[1;32m 566\u001b[0m )\n\u001b[1;32m 567\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 568\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnrecognized configuration class \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mconfig\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m for this kind of AutoModel: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 569\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mModel type should be one of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(c\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mfor\u001b[39;00m\u001b[38;5;250m \u001b[39mc\u001b[38;5;250m \u001b[39m\u001b[38;5;129;01min\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys())\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 570\u001b[0m )\n",
72
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/transformers/modeling_utils.py:3944\u001b[0m, in \u001b[0;36mPreTrainedModel.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, weights_only, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m 3941\u001b[0m \u001b[38;5;66;03m# We'll need to download and cache each checkpoint shard if the checkpoint is sharded.\u001b[39;00m\n\u001b[1;32m 3942\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_sharded:\n\u001b[1;32m 3943\u001b[0m \u001b[38;5;66;03m# resolved_archive_file becomes a list of files that point to the different checkpoint shards in this case.\u001b[39;00m\n\u001b[0;32m-> 3944\u001b[0m resolved_archive_file, sharded_metadata \u001b[38;5;241m=\u001b[39m get_checkpoint_shard_files(\n\u001b[1;32m 3945\u001b[0m pretrained_model_name_or_path,\n\u001b[1;32m 3946\u001b[0m resolved_archive_file,\n\u001b[1;32m 3947\u001b[0m cache_dir\u001b[38;5;241m=\u001b[39mcache_dir,\n\u001b[1;32m 3948\u001b[0m force_download\u001b[38;5;241m=\u001b[39mforce_download,\n\u001b[1;32m 3949\u001b[0m proxies\u001b[38;5;241m=\u001b[39mproxies,\n\u001b[1;32m 3950\u001b[0m resume_download\u001b[38;5;241m=\u001b[39mresume_download,\n\u001b[1;32m 3951\u001b[0m local_files_only\u001b[38;5;241m=\u001b[39mlocal_files_only,\n\u001b[1;32m 3952\u001b[0m token\u001b[38;5;241m=\u001b[39mtoken,\n\u001b[1;32m 3953\u001b[0m user_agent\u001b[38;5;241m=\u001b[39muser_agent,\n\u001b[1;32m 3954\u001b[0m revision\u001b[38;5;241m=\u001b[39mrevision,\n\u001b[1;32m 3955\u001b[0m subfolder\u001b[38;5;241m=\u001b[39msubfolder,\n\u001b[1;32m 3956\u001b[0m _commit_hash\u001b[38;5;241m=\u001b[39mcommit_hash,\n\u001b[1;32m 3957\u001b[0m )\n\u001b[1;32m 3959\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\n\u001b[1;32m 3960\u001b[0m is_safetensors_available()\n\u001b[1;32m 3961\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(resolved_archive_file, \u001b[38;5;28mstr\u001b[39m)\n\u001b[1;32m 3962\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m resolved_archive_file\u001b[38;5;241m.\u001b[39mendswith(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.safetensors\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 3963\u001b[0m ):\n\u001b[1;32m 3964\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m safe_open(resolved_archive_file, framework\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpt\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m f:\n",
73
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/transformers/utils/hub.py:1098\u001b[0m, in \u001b[0;36mget_checkpoint_shard_files\u001b[0;34m(pretrained_model_name_or_path, index_filename, cache_dir, force_download, proxies, resume_download, local_files_only, token, user_agent, revision, subfolder, _commit_hash, **deprecated_kwargs)\u001b[0m\n\u001b[1;32m 1095\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m shard_filename \u001b[38;5;129;01min\u001b[39;00m tqdm(shard_filenames, desc\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDownloading shards\u001b[39m\u001b[38;5;124m\"\u001b[39m, disable\u001b[38;5;241m=\u001b[39m\u001b[38;5;129;01mnot\u001b[39;00m show_progress_bar):\n\u001b[1;32m 1096\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1097\u001b[0m \u001b[38;5;66;03m# Load from URL\u001b[39;00m\n\u001b[0;32m-> 1098\u001b[0m cached_filename \u001b[38;5;241m=\u001b[39m cached_file(\n\u001b[1;32m 1099\u001b[0m pretrained_model_name_or_path,\n\u001b[1;32m 1100\u001b[0m shard_filename,\n\u001b[1;32m 1101\u001b[0m cache_dir\u001b[38;5;241m=\u001b[39mcache_dir,\n\u001b[1;32m 1102\u001b[0m force_download\u001b[38;5;241m=\u001b[39mforce_download,\n\u001b[1;32m 1103\u001b[0m proxies\u001b[38;5;241m=\u001b[39mproxies,\n\u001b[1;32m 1104\u001b[0m resume_download\u001b[38;5;241m=\u001b[39mresume_download,\n\u001b[1;32m 1105\u001b[0m local_files_only\u001b[38;5;241m=\u001b[39mlocal_files_only,\n\u001b[1;32m 1106\u001b[0m token\u001b[38;5;241m=\u001b[39mtoken,\n\u001b[1;32m 1107\u001b[0m user_agent\u001b[38;5;241m=\u001b[39muser_agent,\n\u001b[1;32m 1108\u001b[0m revision\u001b[38;5;241m=\u001b[39mrevision,\n\u001b[1;32m 1109\u001b[0m subfolder\u001b[38;5;241m=\u001b[39msubfolder,\n\u001b[1;32m 1110\u001b[0m _commit_hash\u001b[38;5;241m=\u001b[39m_commit_hash,\n\u001b[1;32m 1111\u001b[0m )\n\u001b[1;32m 1112\u001b[0m \u001b[38;5;66;03m# We have already dealt with RepositoryNotFoundError and RevisionNotFoundError when getting the index, so\u001b[39;00m\n\u001b[1;32m 1113\u001b[0m \u001b[38;5;66;03m# we don't have to catch them here.\u001b[39;00m\n\u001b[1;32m 1114\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m EntryNotFoundError:\n",
74
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/transformers/utils/hub.py:403\u001b[0m, in \u001b[0;36mcached_file\u001b[0;34m(path_or_repo_id, filename, cache_dir, force_download, resume_download, proxies, token, revision, local_files_only, subfolder, repo_type, user_agent, _raise_exceptions_for_gated_repo, _raise_exceptions_for_missing_entries, _raise_exceptions_for_connection_errors, _commit_hash, **deprecated_kwargs)\u001b[0m\n\u001b[1;32m 400\u001b[0m user_agent \u001b[38;5;241m=\u001b[39m http_user_agent(user_agent)\n\u001b[1;32m 401\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 402\u001b[0m \u001b[38;5;66;03m# Load from URL or cache if already cached\u001b[39;00m\n\u001b[0;32m--> 403\u001b[0m resolved_file \u001b[38;5;241m=\u001b[39m hf_hub_download(\n\u001b[1;32m 404\u001b[0m path_or_repo_id,\n\u001b[1;32m 405\u001b[0m filename,\n\u001b[1;32m 406\u001b[0m subfolder\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(subfolder) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m subfolder,\n\u001b[1;32m 407\u001b[0m repo_type\u001b[38;5;241m=\u001b[39mrepo_type,\n\u001b[1;32m 408\u001b[0m revision\u001b[38;5;241m=\u001b[39mrevision,\n\u001b[1;32m 409\u001b[0m cache_dir\u001b[38;5;241m=\u001b[39mcache_dir,\n\u001b[1;32m 410\u001b[0m user_agent\u001b[38;5;241m=\u001b[39muser_agent,\n\u001b[1;32m 411\u001b[0m force_download\u001b[38;5;241m=\u001b[39mforce_download,\n\u001b[1;32m 412\u001b[0m proxies\u001b[38;5;241m=\u001b[39mproxies,\n\u001b[1;32m 413\u001b[0m resume_download\u001b[38;5;241m=\u001b[39mresume_download,\n\u001b[1;32m 414\u001b[0m token\u001b[38;5;241m=\u001b[39mtoken,\n\u001b[1;32m 415\u001b[0m local_files_only\u001b[38;5;241m=\u001b[39mlocal_files_only,\n\u001b[1;32m 416\u001b[0m )\n\u001b[1;32m 417\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m GatedRepoError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 418\u001b[0m resolved_file \u001b[38;5;241m=\u001b[39m _get_cache_file_to_return(path_or_repo_id, full_filename, cache_dir, revision)\n",
75
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/huggingface_hub-0.27.1-py3.8.egg/huggingface_hub/utils/_validators.py:114\u001b[0m, in \u001b[0;36mvalidate_hf_hub_args.<locals>._inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 111\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m check_use_auth_token:\n\u001b[1;32m 112\u001b[0m kwargs \u001b[38;5;241m=\u001b[39m smoothly_deprecate_use_auth_token(fn_name\u001b[38;5;241m=\u001b[39mfn\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, has_token\u001b[38;5;241m=\u001b[39mhas_token, kwargs\u001b[38;5;241m=\u001b[39mkwargs)\n\u001b[0;32m--> 114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m fn(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
76
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/huggingface_hub-0.27.1-py3.8.egg/huggingface_hub/file_download.py:860\u001b[0m, in \u001b[0;36mhf_hub_download\u001b[0;34m(repo_id, filename, subfolder, repo_type, revision, library_name, library_version, cache_dir, local_dir, user_agent, force_download, proxies, etag_timeout, token, local_files_only, headers, endpoint, resume_download, force_filename, local_dir_use_symlinks)\u001b[0m\n\u001b[1;32m 840\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _hf_hub_download_to_local_dir(\n\u001b[1;32m 841\u001b[0m \u001b[38;5;66;03m# Destination\u001b[39;00m\n\u001b[1;32m 842\u001b[0m local_dir\u001b[38;5;241m=\u001b[39mlocal_dir,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 857\u001b[0m local_files_only\u001b[38;5;241m=\u001b[39mlocal_files_only,\n\u001b[1;32m 858\u001b[0m )\n\u001b[1;32m 859\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 860\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _hf_hub_download_to_cache_dir(\n\u001b[1;32m 861\u001b[0m \u001b[38;5;66;03m# Destination\u001b[39;00m\n\u001b[1;32m 862\u001b[0m cache_dir\u001b[38;5;241m=\u001b[39mcache_dir,\n\u001b[1;32m 863\u001b[0m \u001b[38;5;66;03m# File info\u001b[39;00m\n\u001b[1;32m 864\u001b[0m repo_id\u001b[38;5;241m=\u001b[39mrepo_id,\n\u001b[1;32m 865\u001b[0m filename\u001b[38;5;241m=\u001b[39mfilename,\n\u001b[1;32m 866\u001b[0m repo_type\u001b[38;5;241m=\u001b[39mrepo_type,\n\u001b[1;32m 867\u001b[0m revision\u001b[38;5;241m=\u001b[39mrevision,\n\u001b[1;32m 868\u001b[0m \u001b[38;5;66;03m# HTTP info\u001b[39;00m\n\u001b[1;32m 869\u001b[0m endpoint\u001b[38;5;241m=\u001b[39mendpoint,\n\u001b[1;32m 870\u001b[0m etag_timeout\u001b[38;5;241m=\u001b[39metag_timeout,\n\u001b[1;32m 871\u001b[0m headers\u001b[38;5;241m=\u001b[39mhf_headers,\n\u001b[1;32m 872\u001b[0m proxies\u001b[38;5;241m=\u001b[39mproxies,\n\u001b[1;32m 873\u001b[0m token\u001b[38;5;241m=\u001b[39mtoken,\n\u001b[1;32m 874\u001b[0m \u001b[38;5;66;03m# Additional options\u001b[39;00m\n\u001b[1;32m 875\u001b[0m local_files_only\u001b[38;5;241m=\u001b[39mlocal_files_only,\n\u001b[1;32m 876\u001b[0m force_download\u001b[38;5;241m=\u001b[39mforce_download,\n\u001b[1;32m 877\u001b[0m )\n",
77
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/huggingface_hub-0.27.1-py3.8.egg/huggingface_hub/file_download.py:1009\u001b[0m, in \u001b[0;36m_hf_hub_download_to_cache_dir\u001b[0;34m(cache_dir, repo_id, filename, repo_type, revision, endpoint, etag_timeout, headers, proxies, token, local_files_only, force_download)\u001b[0m\n\u001b[1;32m 1007\u001b[0m Path(lock_path)\u001b[38;5;241m.\u001b[39mparent\u001b[38;5;241m.\u001b[39mmkdir(parents\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, exist_ok\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 1008\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m WeakFileLock(lock_path):\n\u001b[0;32m-> 1009\u001b[0m _download_to_tmp_and_move(\n\u001b[1;32m 1010\u001b[0m incomplete_path\u001b[38;5;241m=\u001b[39mPath(blob_path \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.incomplete\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 1011\u001b[0m destination_path\u001b[38;5;241m=\u001b[39mPath(blob_path),\n\u001b[1;32m 1012\u001b[0m url_to_download\u001b[38;5;241m=\u001b[39murl_to_download,\n\u001b[1;32m 1013\u001b[0m proxies\u001b[38;5;241m=\u001b[39mproxies,\n\u001b[1;32m 1014\u001b[0m headers\u001b[38;5;241m=\u001b[39mheaders,\n\u001b[1;32m 1015\u001b[0m expected_size\u001b[38;5;241m=\u001b[39mexpected_size,\n\u001b[1;32m 1016\u001b[0m filename\u001b[38;5;241m=\u001b[39mfilename,\n\u001b[1;32m 1017\u001b[0m force_download\u001b[38;5;241m=\u001b[39mforce_download,\n\u001b[1;32m 1018\u001b[0m )\n\u001b[1;32m 1019\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mexists(pointer_path):\n\u001b[1;32m 1020\u001b[0m _create_symlink(blob_path, pointer_path, new_blob\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n",
78
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/huggingface_hub-0.27.1-py3.8.egg/huggingface_hub/file_download.py:1543\u001b[0m, in \u001b[0;36m_download_to_tmp_and_move\u001b[0;34m(incomplete_path, destination_path, url_to_download, proxies, headers, expected_size, filename, force_download)\u001b[0m\n\u001b[1;32m 1540\u001b[0m _check_disk_space(expected_size, incomplete_path\u001b[38;5;241m.\u001b[39mparent)\n\u001b[1;32m 1541\u001b[0m _check_disk_space(expected_size, destination_path\u001b[38;5;241m.\u001b[39mparent)\n\u001b[0;32m-> 1543\u001b[0m http_get(\n\u001b[1;32m 1544\u001b[0m url_to_download,\n\u001b[1;32m 1545\u001b[0m f,\n\u001b[1;32m 1546\u001b[0m proxies\u001b[38;5;241m=\u001b[39mproxies,\n\u001b[1;32m 1547\u001b[0m resume_size\u001b[38;5;241m=\u001b[39mresume_size,\n\u001b[1;32m 1548\u001b[0m headers\u001b[38;5;241m=\u001b[39mheaders,\n\u001b[1;32m 1549\u001b[0m expected_size\u001b[38;5;241m=\u001b[39mexpected_size,\n\u001b[1;32m 1550\u001b[0m )\n\u001b[1;32m 1552\u001b[0m logger\u001b[38;5;241m.\u001b[39minfo(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDownload complete. Moving file to \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdestination_path\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 1553\u001b[0m _chmod_and_move(incomplete_path, destination_path)\n",
79
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/huggingface_hub-0.27.1-py3.8.egg/huggingface_hub/file_download.py:452\u001b[0m, in \u001b[0;36mhttp_get\u001b[0;34m(url, temp_file, proxies, resume_size, headers, expected_size, displayed_filename, _nb_retries, _tqdm_bar)\u001b[0m\n\u001b[1;32m 450\u001b[0m new_resume_size \u001b[38;5;241m=\u001b[39m resume_size\n\u001b[1;32m 451\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 452\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m chunk \u001b[38;5;129;01min\u001b[39;00m r\u001b[38;5;241m.\u001b[39miter_content(chunk_size\u001b[38;5;241m=\u001b[39mconstants\u001b[38;5;241m.\u001b[39mDOWNLOAD_CHUNK_SIZE):\n\u001b[1;32m 453\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chunk: \u001b[38;5;66;03m# filter out keep-alive new chunks\u001b[39;00m\n\u001b[1;32m 454\u001b[0m progress\u001b[38;5;241m.\u001b[39mupdate(\u001b[38;5;28mlen\u001b[39m(chunk))\n",
80
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/requests/models.py:820\u001b[0m, in \u001b[0;36mResponse.iter_content.<locals>.generate\u001b[0;34m()\u001b[0m\n\u001b[1;32m 818\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mraw, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstream\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[1;32m 819\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 820\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mraw\u001b[38;5;241m.\u001b[39mstream(chunk_size, decode_content\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 821\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ProtocolError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 822\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ChunkedEncodingError(e)\n",
81
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/urllib3/response.py:1066\u001b[0m, in \u001b[0;36mHTTPResponse.stream\u001b[0;34m(self, amt, decode_content)\u001b[0m\n\u001b[1;32m 1064\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1065\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_fp_closed(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_fp) \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_decoded_buffer) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m-> 1066\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mread(amt\u001b[38;5;241m=\u001b[39mamt, decode_content\u001b[38;5;241m=\u001b[39mdecode_content)\n\u001b[1;32m 1068\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m data:\n\u001b[1;32m 1069\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m data\n",
82
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/urllib3/response.py:955\u001b[0m, in \u001b[0;36mHTTPResponse.read\u001b[0;34m(self, amt, decode_content, cache_content)\u001b[0m\n\u001b[1;32m 952\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_decoded_buffer) \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m amt:\n\u001b[1;32m 953\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_decoded_buffer\u001b[38;5;241m.\u001b[39mget(amt)\n\u001b[0;32m--> 955\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_raw_read(amt)\n\u001b[1;32m 957\u001b[0m flush_decoder \u001b[38;5;241m=\u001b[39m amt \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mor\u001b[39;00m (amt \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m data)\n\u001b[1;32m 959\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m data \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_decoded_buffer) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n",
83
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/urllib3/response.py:879\u001b[0m, in \u001b[0;36mHTTPResponse._raw_read\u001b[0;34m(self, amt, read1)\u001b[0m\n\u001b[1;32m 876\u001b[0m fp_closed \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_fp, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mclosed\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m 878\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_error_catcher():\n\u001b[0;32m--> 879\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_fp_read(amt, read1\u001b[38;5;241m=\u001b[39mread1) \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m fp_closed \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 880\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m amt \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m amt \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m data:\n\u001b[1;32m 881\u001b[0m \u001b[38;5;66;03m# Platform-specific: Buggy versions of Python.\u001b[39;00m\n\u001b[1;32m 882\u001b[0m \u001b[38;5;66;03m# Close the connection when no data is returned\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 887\u001b[0m \u001b[38;5;66;03m# not properly close the connection in all cases. There is\u001b[39;00m\n\u001b[1;32m 888\u001b[0m \u001b[38;5;66;03m# no harm in redundantly calling close.\u001b[39;00m\n\u001b[1;32m 889\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_fp\u001b[38;5;241m.\u001b[39mclose()\n",
84
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/site-packages/urllib3/response.py:862\u001b[0m, in \u001b[0;36mHTTPResponse._fp_read\u001b[0;34m(self, amt, read1)\u001b[0m\n\u001b[1;32m 859\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_fp\u001b[38;5;241m.\u001b[39mread1(amt) \u001b[38;5;28;01mif\u001b[39;00m amt \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_fp\u001b[38;5;241m.\u001b[39mread1()\n\u001b[1;32m 860\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 861\u001b[0m \u001b[38;5;66;03m# StringIO doesn't like amt=None\u001b[39;00m\n\u001b[0;32m--> 862\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_fp\u001b[38;5;241m.\u001b[39mread(amt) \u001b[38;5;28;01mif\u001b[39;00m amt \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_fp\u001b[38;5;241m.\u001b[39mread()\n",
85
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/http/client.py:479\u001b[0m, in \u001b[0;36mHTTPResponse.read\u001b[0;34m(self, amt)\u001b[0m\n\u001b[1;32m 476\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlength \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m amt \u001b[38;5;241m>\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlength:\n\u001b[1;32m 477\u001b[0m \u001b[38;5;66;03m# clip the read to the \"end of response\"\u001b[39;00m\n\u001b[1;32m 478\u001b[0m amt \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlength\n\u001b[0;32m--> 479\u001b[0m s \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfp\u001b[38;5;241m.\u001b[39mread(amt)\n\u001b[1;32m 480\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m s \u001b[38;5;129;01mand\u001b[39;00m amt:\n\u001b[1;32m 481\u001b[0m \u001b[38;5;66;03m# Ideally, we would raise IncompleteRead if the content-length\u001b[39;00m\n\u001b[1;32m 482\u001b[0m \u001b[38;5;66;03m# wasn't satisfied, but it might break compatibility.\u001b[39;00m\n\u001b[1;32m 483\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_close_conn()\n",
86
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/socket.py:707\u001b[0m, in \u001b[0;36mSocketIO.readinto\u001b[0;34m(self, b)\u001b[0m\n\u001b[1;32m 705\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[1;32m 706\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 707\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sock\u001b[38;5;241m.\u001b[39mrecv_into(b)\n\u001b[1;32m 708\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m timeout:\n\u001b[1;32m 709\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_timeout_occurred \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
87
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/ssl.py:1252\u001b[0m, in \u001b[0;36mSSLSocket.recv_into\u001b[0;34m(self, buffer, nbytes, flags)\u001b[0m\n\u001b[1;32m 1248\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m flags \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 1249\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 1250\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnon-zero flags not allowed in calls to recv_into() on \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m\n\u001b[1;32m 1251\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m)\n\u001b[0;32m-> 1252\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mread(nbytes, buffer)\n\u001b[1;32m 1253\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1254\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39mrecv_into(buffer, nbytes, flags)\n",
88
+ "File \u001b[0;32m~/miniconda3/envs/py312/lib/python3.12/ssl.py:1104\u001b[0m, in \u001b[0;36mSSLSocket.read\u001b[0;34m(self, len, buffer)\u001b[0m\n\u001b[1;32m 1102\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1103\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m buffer \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 1104\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sslobj\u001b[38;5;241m.\u001b[39mread(\u001b[38;5;28mlen\u001b[39m, buffer)\n\u001b[1;32m 1105\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1106\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sslobj\u001b[38;5;241m.\u001b[39mread(\u001b[38;5;28mlen\u001b[39m)\n",
89
+ "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
90
+ ]
91
+ }
92
+ ],
93
+ "source": [
94
+ "import torch\n",
95
+ "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
96
+ "from peft import PeftModel\n",
97
+ "import os\n",
98
+ "import gc\n",
99
+ "\n",
100
+ "# === 1. 环境准备 (MPS) ===\n",
101
+ "# 必须先 Restart Kernel，否则这里会报错\n",
102
+ "device = torch.device(\"mps\")\n",
103
+ "print(f\"🚀 环境已重置，使用设备: {device}\")\n",
104
+ "\n",
105
+ "# === 2. 加载模型 (MPS + Float16) ===\n",
106
+ "model_id = \"psychologyphd/CodeLlama-7b-Text-to-SQL-mps-finetuned\"\n",
107
+ "\n",
108
+ "\n",
109
+ "print(\"⏳ 正在加载模型 (MPS + Float16)...\")\n",
110
+ "\n",
111
+ "# 加载 Base Model\n",
112
+ "model = AutoModelForCausalLM.from_pretrained(\n",
113
+ " model_id,\n",
114
+ " device_map={\"\": device}, \n",
115
+ " torch_dtype=torch.float16, # 半精度，省显存\n",
116
+ ")\n",
117
+ "\n",
118
+ "\n",
119
+ "model.eval()\n",
120
+ "\n",
121
+ "# 加载 Tokenizer\n",
122
+ "tokenizer = AutoTokenizer.from_pretrained(base_model_id)\n",
123
+ "if tokenizer.pad_token is None:\n",
124
+ " tokenizer.pad_token = tokenizer.eos_token\n",
125
+ "\n",
126
+ "print(\"✅ 模型加载完毕\")\n",
127
+ "\n",
128
+ "# === 3. 构造【修复版】Prompt ===\n",
129
+ "# ⚠️ 关键点：这里严格保证了 SCHEMA 后的换行符\n",
130
+ "test_schema = \"CREATE TABLE table_name_66 (place VARCHAR, money___£__ VARCHAR, score VARCHAR)\"\n",
131
+ "test_question = \"What is the place of the player with £140,000 and a 68-68-75-68=279 score?\"\n",
132
+ "\n",
133
+ "prompt_manual = f\"### System: You are an text to SQL query translator. Users will ask you questions in English and you will generate a SQL query based on the provided SCHEMA.\\nSCHEMA:\\n{test_schema}\\n\"\n",
134
+ "prompt_manual += f\"### Human: {test_question}\\n\"\n",
135
+ "prompt_manual += \"### Assistant: \"\n",
136
+ "\n",
137
+ "print(f\"\\n🔍 Prompt (确认已有换行):\\n{prompt_manual}\\n{'='*20}\")\n",
138
+ "\n",
139
+ "# === 4. 生成 (带重复惩罚) ===\n",
140
+ "inputs = tokenizer(prompt_manual, return_tensors=\"pt\").to(device)\n",
141
+ "\n",
142
+ "print(\"🤖 正在生成 (MPS Fast Mode)...\")\n",
143
+ "with torch.no_grad():\n",
144
+ " outputs = model.generate(\n",
145
+ " **inputs,\n",
146
+ " max_new_tokens=100,\n",
147
+ " do_sample=True, # 开启采样以支持 repetition_penalty\n",
148
+ " temperature=0.1, # 低温，保持生成的 SQL 准确\n",
149
+ " top_p=0.95,\n",
150
+ " repetition_penalty=1.2, # 🔴 强力压制复读机\n",
151
+ " pad_token_id=tokenizer.pad_token_id,\n",
152
+ " eos_token_id=tokenizer.eos_token_id\n",
153
+ " )\n",
154
+ "\n",
155
+ "# === 5. 解码 ===\n",
156
+ "result = tokenizer.decode(outputs[0], skip_special_tokens=True)\n",
157
+ "if \"### Assistant:\" in result:\n",
158
+ " final_sql = result.split(\"### Assistant:\")[-1].strip()\n",
159
+ "else:\n",
160
+ " final_sql = result[len(prompt_manual):].strip()\n",
161
+ "\n",
162
+ "print(f\"\\n💡 生成结果:\\n{final_sql}\")"
163
+ ]
164
+ },
165
+ {
166
+ "cell_type": "markdown",
167
+ "id": "7cd8644d",
168
+ "metadata": {},
169
+ "source": [
170
+ "it can gernerate results like the following. \n",
171
+ "it is able to under stand from the begining that the task is to generate sql by generating \"select place\". \n",
172
+ "however it is overfitting that resulted in repeated users and \\\\\\\\\\. \n",
173
+ "The \"import\" is from the base model codellama that was fine tuned on python\n",
174
+ "💡 生成结果:\n",
175
+ "SELECT place tagUsersusers Users \\\\3\\\\ Users Users\\\\­\\\\\\\\\\\\\\\\\\\\ Users Users Users\\\\\\\\\\\\\\\\ //\\\\\\\\ Users\\\\ Users Users\\\\\\\\\\\\\\\\ # \\\\\\\\\\\\\\\\\\\\\\\\\\\\ \\\\\\\\ <? Users\\\\\\\\\\\\\\\\\\\\\\\\ \\\\ \\\\\\\\\\\\\\\\ Users\\\\ Users package\\\\ Users\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ <\\\\\\\\ import\\\\\\\\\\\\\\\\ \\\\ --- '\\\\\\\\\\\\\\\\ \\\\"
176
+ ]
177
+ },
178
+ {
179
+ "cell_type": "markdown",
180
+ "id": "a3a8f0e3",
181
+ "metadata": {},
182
+ "source": []
183
+ },
184
+ {
185
+ "cell_type": "markdown",
186
+ "id": "822babe2",
187
+ "metadata": {},
188
+ "source": []
189
+ }
190
+ ],
191
+ "metadata": {
192
+ "kernelspec": {
193
+ "display_name": "Python 3.12.2",
194
+ "language": "python",
195
+ "name": "py312"
196
+ },
197
+ "language_info": {
198
+ "codemirror_mode": {
199
+ "name": "ipython",
200
+ "version": 3
201
+ },
202
+ "file_extension": ".py",
203
+ "mimetype": "text/x-python",
204
+ "name": "python",
205
+ "nbconvert_exporter": "python",
206
+ "pygments_lexer": "ipython3",
207
+ "version": "3.12.2"
208
+ }
209
+ },
210
+ "nbformat": 4,
211
+ "nbformat_minor": 5
212
+ }