/home/matt/hf/sqllama-V0/.venv/lib/python3.7/site-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: /opt/conda did not contain libcudart.so as expected! Searching further paths... warn(msg) The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. The tokenizer class you load from this checkpoint is 'LLaMATokenizer'. The class this function is called from is 'LlamaTokenizer'. ===================================BUG REPORT=================================== Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues ================================================================================ CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so CUDA SETUP: Highest compute capability among GPUs detected: 7.5 CUDA SETUP: Detected CUDA version 113 CUDA SETUP: Loading binary /home/matt/hf/sqllama-V0/.venv/lib/python3.7/site-packages/bitsandbytes/libbitsandbytes_cuda113.so... Output exceeds the size limit. Open the full output data in a text editor table: 2-16050349-13 columns: Rank,Name,Team,Games,Points Q: What is Games, when Points is less than 340, and when Rank is greater than 3? A: SELECT Games FROM 2-16050349-13 WHERE Points < 340 AND Rank > 3 END table: 1-28962227-1 columns: Series,Premiere,Finale,Runners-up,Winner Q: What is the date of the finale where Holly Bell was runner-up? A: SELECT Finale FROM 1-28962227-1 WHERE Runners-up = 'Holly Bell' END table: 2-10652530-2 columns: Week,Date,Opponent,Result,Stadium,Record,Attendance Q: What was the Browns record after they played the game at the Paul Brown stadium? A: SELECT Record FROM 2-10652530-2 WHERE Stadium = 'paul brown stadium' END table: 2-18379129-4 columns: play,author,company,base,country Q: Who is the author of the Play Electra? ... Q: What is 02-03, when School Year is % Learning In Latvian? A: SELECT 02-03 FROM 2-16158579-1 WHERE School year = '% learning in latvian' END True 92 0 count 56355.000000 mean 101.219519 std 21.740325 min 63.000000 25% 87.500000 50% 97.000000 75% 109.000000 max 461.000000 32084 [500/500 7:38:36, Epoch 1/2] Step Training Loss 1 2.748800 2 2.723800 3 2.737600 4 2.707100 5 2.692800 6 2.720700 7 2.681400 8 2.736400 9 2.701800 10 2.711700 11 2.685800 12 2.684300 13 2.686300 14 2.698800 15 2.659300 16 2.688900 17 2.661800 18 2.677700 19 2.647100 20 2.679800 21 2.652000 22 2.628900 23 2.656100 24 2.669100 25 2.667800 26 2.636300 27 2.616800 28 2.630600 29 2.621000 30 2.602000 31 2.607900 32 2.635800 33 2.594600 34 2.604400 35 2.618900 36 2.563400 37 2.589200 38 2.552100 39 2.583600 40 2.554500 41 2.557400 42 2.536700 43 2.535000 44 2.557900 45 2.530100 46 2.527900 47 2.510100 48 2.539100 49 2.500100 50 2.536200 51 2.487100 52 2.521700 53 2.532600 54 2.494500 55 2.468900 56 2.468700 57 2.474300 58 2.480900 59 2.442800 60 2.472800 61 2.452900 62 2.452000 63 2.443100 64 2.446700 65 2.415100 66 2.376300 67 2.411500 68 2.403900 69 2.383800 70 2.427800 71 2.419400 72 2.371900 73 2.364400 74 2.360000 75 2.337600 76 2.332800 77 2.315700 78 2.344200 79 2.331700 80 2.303100 81 2.324700 82 2.285900 83 2.268000 84 2.260600 85 2.286100 86 2.233600 87 2.266200 88 2.217000 89 2.249300 90 2.239000 91 2.221900 92 2.223300 93 2.179500 94 2.204400 95 2.193200 96 2.163800 97 2.158200 98 2.127700 99 2.141400 100 2.121400 101 2.115500 102 2.125200 103 2.140100 104 2.118400 105 2.110400 106 2.097300 107 2.071400 108 2.083400 109 2.090200 110 2.078200 111 2.061100 112 2.047500 113 2.006100 114 2.023800 115 2.014000 116 2.008800 117 1.988800 118 1.984900 119 1.971000 120 1.924100 121 1.953100 122 1.957800 123 1.952500 124 1.890400 125 1.915900 126 1.901100 127 1.879900 128 1.834100 129 1.855900 130 1.853800 131 1.869200 132 1.821400 133 1.835100 134 1.817700 135 1.785800 136 1.764000 137 1.796800 138 1.751100 139 1.756500 140 1.789900 141 1.773100 142 1.729200 143 1.700200 144 1.721200 145 1.690600 146 1.687700 147 1.743500 148 1.690000 149 1.687200 150 1.663000 151 1.648600 152 1.667100 153 1.665600 154 1.647000 155 1.629500 156 1.620800 157 1.616400 158 1.658500 159 1.593900 160 1.604300 161 1.621200 162 1.607900 163 1.591100 164 1.598100 165 1.579700 166 1.545500 167 1.582100 168 1.568300 169 1.557900 170 1.561300 171 1.521800 172 1.542500 173 1.502300 174 1.513900 175 1.501500 176 1.551200 177 1.495600 178 1.504000 179 1.512500 180 1.488200 181 1.492200 182 1.494300 183 1.494800 184 1.446100 185 1.514700 186 1.450900 187 1.476900 188 1.447100 189 1.490800 190 1.433200 191 1.438100 192 1.410500 193 1.422600 194 1.405500 195 1.439400 196 1.448100 197 1.410200 198 1.403800 199 1.464400 200 1.417700 201 1.419500 202 1.419400 203 1.387700 204 1.400400 205 1.404700 206 1.398400 207 1.358000 208 1.359600 209 1.367700 210 1.358600 211 1.369200 212 1.373700 213 1.395100 214 1.360800 215 1.343900 216 1.330300 217 1.328800 218 1.369900 219 1.346300 220 1.379700 221 1.326000 222 1.334600 223 1.339100 224 1.349200 225 1.324800 226 1.303600 227 1.299900 228 1.338800 229 1.331800 230 1.351400 231 1.314200 232 1.293600 233 1.322100 234 1.295800 235 1.302500 236 1.338900 237 1.308900 238 1.290100 239 1.323300 240 1.270500 241 1.246300 242 1.303900 243 1.324800 244 1.216000 245 1.303500 246 1.304900 247 1.273300 248 1.278300 249 1.252000 250 1.283400 251 1.271600 252 1.300300 253 1.265800 254 1.249200 255 1.252600 256 1.265500 257 1.228600 258 1.257300 259 1.288900 260 1.257200 261 1.243700 262 1.272100 263 1.252000 264 1.264900 265 1.268800 266 1.256000 267 1.230200 268 1.231700 269 1.243400 270 1.285200 271 1.225500 272 1.217900 273 1.209200 274 1.224200 275 1.226400 276 1.261500 277 1.223900 278 1.244000 279 1.226600 280 1.235000 281 1.213400 282 1.177600 283 1.218100 284 1.231900 285 1.200900 286 1.223400 287 1.235100 288 1.232500 289 1.230100 290 1.225900 291 1.182700 292 1.237100 293 1.201000 294 1.213000 295 1.205500 296 1.181900 297 1.198300 298 1.195200 299 1.215000 300 1.195500 301 1.186100 302 1.174900 303 1.184400 304 1.207100 305 1.181100 306 1.195300 307 1.189000 308 1.180200 309 1.167200 310 1.206700 311 1.203600 312 1.186600 313 1.224100 314 1.180000 315 1.186600 316 1.150700 317 1.165700 318 1.178100 319 1.148300 320 1.153600 321 1.189200 322 1.182100 323 1.183800 324 1.202900 325 1.196600 326 1.200800 327 1.153100 328 1.212400 329 1.167300 330 1.188300 331 1.179300 332 1.211400 333 1.169900 334 1.179300 335 1.153300 336 1.188900 337 1.179200 338 1.217300 339 1.169700 340 1.177700 341 1.197300 342 1.177800 343 1.169700 344 1.186800 345 1.180000 346 1.193400 347 1.171900 348 1.190000 349 1.160900 350 1.170800 351 1.166900 352 1.183200 353 1.118200 354 1.185900 355 1.157800 356 1.160200 357 1.184200 358 1.172100 359 1.143800 360 1.178000 361 1.157900 362 1.151700 363 1.196600 364 1.181800 365 1.195600 366 1.165000 367 1.157300 368 1.165200 369 1.167700 370 1.184900 371 1.168400 372 1.150500 373 1.152900 374 1.158900 375 1.143900 376 1.157200 377 1.146800 378 1.142600 379 1.140600 380 1.142400 381 1.114100 382 1.169700 383 1.142500 384 1.176000 385 1.160600 386 1.164700 387 1.124000 388 1.134500 389 1.185500 390 1.154300 391 1.125500 392 1.174400 393 1.132800 394 1.145200 395 1.129800 396 1.140600 397 1.126000 398 1.182800 399 1.127800 400 1.155000 401 1.134600 402 1.155900 403 1.150400 404 1.141700 405 1.131500 406 1.169600 407 1.170500 408 1.129100 409 1.151700 410 1.168200 411 1.109100 412 1.129700 413 1.143900 414 1.157300 415 1.128900 416 1.171500 417 1.141600 418 1.157700 419 1.137000 420 1.154000 421 1.167300 422 1.137400 423 1.121500 424 1.128500 425 1.130300 426 1.162100 427 1.155100 428 1.145300 429 1.121000 430 1.182200 431 1.157000 432 1.162300 433 1.135200 434 1.141300 435 1.151700 436 1.148000 437 1.132500 438 1.163000 439 1.116300 440 1.142000 441 1.091700 442 1.141500 443 1.154900 444 1.120400 445 1.173700 446 1.138300 447 1.135600 448 1.138800 449 1.126800 450 1.129400 451 1.146300 452 1.104200 453 1.163500 454 1.169300 455 1.147100 456 1.157100 457 1.122100 458 1.121900 459 1.150500 460 1.115700 461 1.121100 462 1.123400 463 1.097500 464 1.103800 465 1.167700 466 1.130000 467 1.164500 468 1.127200 469 1.133800 470 1.132700 471 1.122800 472 1.159500 473 1.122900 474 1.105000 475 1.145700 476 1.086400 477 1.112600 478 1.139300 479 1.135000 480 1.135200 481 1.117500 482 1.102300 483 1.147700 484 1.119200 485 1.125800 486 1.135400 487 1.149500 488 1.099400 489 1.153900 490 1.122700 491 1.089400 492 1.167200 493 1.151300 494 1.131400 495 1.131400 496 1.145200 497 1.125700 498 1.119300 499 1.128600 500 1.121000 /home/matt/hf/sqllama-V0/.venv/lib/python3.7/site-packages/transformers/generation/utils.py:1220: UserWarning: You have modified the pretrained model configuration to control generation. This is a deprecated strategy to control generation and will be removed soon, in a future version. Please use a generation configuration file (see https://huggingface.co/docs/transformers/main_classes/text_generation) "You have modified the pretrained model configuration to control generation. This is a" /home/matt/hf/sqllama-V0/.venv/lib/python3.7/site-packages/torch/utils/checkpoint.py:31: UserWarning: None of the inputs have requires_grad=True. Gradients will be None warnings.warn("None of the inputs have requires_grad=True. Gradients will be None") Output exceeds the size limit. Open the full output data in a text editor from model table: 2-11561331-17 columns: Name,Actual version,System,Platform,License Q: Which System's Name is Steem, and has a Freeware License? A: SELECT Name FROM 2-11561331-17 WHERE License = 'Freeware' AND System = 'Steem' END \end{code} expected answer SELECT System FROM 2-11561331-17 WHERE License = 'freeware' AND Name = 'steem' END from model table: 1-18847736-2 columns: Game,Date,Opponent,Result,Dolphins points,Opponents,Record,Attendance Q: What is the date when the opponent is the New England Patriots? A: SELECT Date FROM 1-18847736-2 WHERE Opponent = 'New England Patriots' END \end expected answer SELECT Date FROM 1-18847736-2 WHERE Opponent = 'New England Patriots' END ... expected answer SELECT Manufacturer FROM 1-17801022-1 WHERE Date = 'November 2' END