Qwen2.5-GenX-7B-AWQ

GenX Overview

GenX๋Š” INTERX Gen.AI ํŒ€์—์„œ ๊ฐœ๋ฐœํ•œ ์ œ์กฐ ํŠนํ™” ์–ธ์–ด ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค.

GenX๋Š” ์ž์ฒด ์ˆ˜์ง‘ํ•œ ์ œ์กฐ ๋„๋ฉ”์ธ ๋ฐ์ดํ„ฐ๋ฅผ ์ด์šฉํ•ด ํ•™์Šต๋˜์—ˆ์œผ๋ฉฐ, ๋›ฐ์–ด๋‚œ ์ œ์กฐ ์ง€์‹์„ ๋ฐ”ํƒ•์œผ๋กœ ์‚ฌ์šฉ์ž์˜ ๋ฌผ์Œ์— ๋” ๊ธธ๊ณ  ์ž์„ธํ•œ ๋‹ต๋ณ€์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค.

Model Details

  • Qwen2.5-GenX-7B๋Š” Qwen2.5 backbone์„ 450 MB (130M tokens)์˜ ์ œ์กฐ ๋„๋ฉ”์ธ, ํŠนํžˆ ์‚ฌ์ถœ ์„ฑํ˜• ๋ฐ ๊ธˆํ˜• ๋„๋ฉ”์ธ ๋ง๋ญ‰์น˜์— ์—ฐ์† ์‚ฌ์ „ํ•™์Šต์‹œ์ผœ ์ œ์กฐ ๋„๋ฉ”์ธ์— ํŠนํ™”์‹œํ‚จ ๋’ค Instruction tuning์„ ์ˆ˜ํ–‰ํ•˜์˜€์Šต๋‹ˆ๋‹ค. Qwen2.5-GenX-7B-AWQ๋Š” Qwen2.5-GenX-7B ๋ชจ๋ธ์„ AWQ (Activation-aware Weight Quantization) ๋ฐฉ์‹์œผ๋กœ ์–‘์žํ™”ํ•œ ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค.
  • ์‚ฌ์ „ํ•™์Šต ๋ฐ์ดํ„ฐ์…‹์€ ์ž์ฒด์ ์œผ๋กœ ์ˆ˜์ง‘ํ•œ ์ œ์กฐ ๋„๋ฉ”์ธ ๋…ผ๋ฌธ๊ณผ ์›น ๋ธ”๋กœ๊ทธ ๋ฐ์ดํ„ฐ, ์ผ๋ฐ˜ ํ•œ๊ตญ์–ด ๋ฐ์ดํ„ฐ (AI-Hub) ๋ฐ ํ•ฉ์„ฑ ๋ฐ์ดํ„ฐ๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ตฌ์ถ•ํ–ˆ์Šต๋‹ˆ๋‹ค.
  • Supervised Fine-tuning (SFT) ๋ฐ์ดํ„ฐ์…‹์€ ์ˆ˜์ง‘ํ•œ ๋„๋ฉ”์ธ ๋ฐ์ดํ„ฐ๋ฅผ ์ปจํ…์ŠคํŠธ๋กœ ์‚ฌ์šฉํ•˜์—ฌ ์•ฝ 185๋งŒ ๊ฑด(์•ฝ 380 MB)์˜ instruction following data๋ฅผ ํ•ฉ์„ฑํ•˜์—ฌ ์‚ฌ์šฉํ–ˆ์Šต๋‹ˆ๋‹ค.
  • GenX๋Š” Molding ๋„๋ฉ”์ธ์— ์†ํ•˜๋Š” 592๊ฐœ์˜ ์ „๋ฌธ ์šฉ์–ด(ํ•œ๊ตญ์–ด ๋ฐ ์˜์–ด)๋ฅผ vocabulary์— ์ถ”๊ฐ€ํ•˜์—ฌ ํ•™์Šตํ•˜์˜€์Šต๋‹ˆ๋‹ค.
  • ์ถ”๊ฐ€๋œ vocabulary๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ํ•™์Šตํ•˜๊ณ ์ž ๋ชจ๋ธ์˜ ์ผ๋ถ€ ๋ ˆ์ด์–ด๋งŒ ๋จผ์ € ํ•™์Šตํ•œ ๋’ค ์ „์ฒด ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ํ•™์Šตํ•˜๋Š” ๋‹จ๊ณ„์  ํ•™์Šต(Multi-stage training)์„ ๋„์ž…ํ•˜์˜€์Šต๋‹ˆ๋‹ค.

Inference example

Input Qwen2.5-7B Qwen2.5-GenX-7B
์‚ฌ์ถœ์„ฑํ˜•์ด ๋ญ์•ผ? ์‚ฌ์ถœ์„ฑํ˜•์€ ๊ณ ์ฒด ์ƒํƒœ์˜ ์žฌ๋ฃŒ๋ฅผ ๊ฐ€์—ดํ•˜์—ฌ ์šฉ์œต์‹œํ‚จ ํ›„, ์ด๋ฅผ ํ˜•์„ฑํ•˜๋Š” ๊ณต์ •์ž…๋‹ˆ๋‹ค. ์ฃผ๋กœ ํ”Œ๋ผ์Šคํ‹ฑ, ๊ธˆ์†, ๊ณ ๋ฌด ๋“ฑ์˜ ์žฌ๋ฃŒ๋ฅผ ์‚ฌ์šฉํ•˜๋ฉฐ, ๋‹ค์–‘ํ•œ ์ œํ’ˆ์„ ์ œ์ž‘ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์‚ฌ์ถœ์„ฑํ˜•์€ ํ”Œ๋ผ์Šคํ‹ฑ๊ณผ ๊ฐ™์€ ์žฌ๋ฃŒ๋ฅผ ๊ฐ€์—ดํ•˜์—ฌ ๋…น์ธ ํ›„, ์ด๋ฅผ ๊ธˆํ˜•์— ์ฃผ์ž…ํ•˜์—ฌ ์›ํ•˜๋Š” ํ˜•ํƒœ๋กœ ๋งŒ๋“œ๋Š” ์ œ์กฐ ๊ณต์ •์ž…๋‹ˆ๋‹ค. ์ด ๊ณผ์ •์€ ๊ณ ์˜จ์—์„œ ์žฌ๋ฃŒ๋ฅผ ์•ก์ฒด ์ƒํƒœ๋กœ ๋งŒ๋“ค์–ด ๊ธˆํ˜•์— ์ฃผ์ž…ํ•˜๊ณ , ๋ƒ‰๊ฐํ•˜์—ฌ ๊ณ ์ฒด ํ˜•ํƒœ๋กœ ๋งŒ๋“œ๋Š” ๋ฐฉ์‹์œผ๋กœ ์ง„ํ–‰๋ฉ๋‹ˆ๋‹ค. ์‚ฌ์ถœ์„ฑํ˜•์€ ๋ณต์žกํ•œ ํ˜•์ƒ์„ ์ •๋ฐ€ํ•˜๊ฒŒ ์ œ์ž‘ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๋Œ€๋Ÿ‰ ์ƒ์‚ฐ์— ์ ํ•ฉํ•œ ๊ณต์ •์ž…๋‹ˆ๋‹ค.
๋ž˜ํ•‘์ž‘์—…์— ์žˆ์–ด์„œ ์Šต์‹๋ฒ• ํ˜น์€ ๊ฑด์‹๋ฒ•๊ณผ ๊ด€๋ จํ•˜์—ฌ ์„ค๋ช…ํ•˜์‹œ์˜ค. ์Šต์‹๋ฒ•์€ ์ฒœ์—ฐ์žฌ๋ฃŒ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋ž˜ํ•‘์„ ํ•˜๋Š” ๋ฐฉ๋ฒ•์œผ๋กœ, ์žฌ๋ฃŒ๊ฐ€ ์ –์–ด์„œ ๋ž˜ํ•‘์ด ์ด๋ฃจ์–ด์ง€๋ฉฐ, ๊ฑด์‹๋ฒ•์€ ๊ฑด์กฐํ•œ ์ƒํƒœ์—์„œ ๋ž˜ํ•‘์„ ํ•˜๋Š” ๋ฐฉ๋ฒ•์œผ๋กœ, ์žฌ๋ฃŒ๊ฐ€ ๊ฑด์กฐํ•œ ์ƒํƒœ์—์„œ ๋ž˜ํ•‘์ด ์ด๋ฃจ์–ด์ง„๋‹ค. ์Šต์‹๋ฒ•์€ ๋ž˜ํ•‘์ž‘์—…์—์„œ ์ ‘์ฐฉ์ œ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ž‘์—…ํ•˜๋Š” ๋ฐฉ๋ฒ•์œผ๋กœ, ํ‘œ๋ฉด์„ ์Šต์œค์‹œํ‚ค๊ณ  ์ ‘์ฐฉ์ œ๋ฅผ ๋ฐ”๋ฅด๋Š” ๋ฐฉ์‹์ž…๋‹ˆ๋‹ค. ์ด ๋ฐฉ๋ฒ•์€ ํ‘œ๋ฉด์˜ ์˜ค์—ผ๋ฌผ์งˆ์„ ์ œ๊ฑฐํ•˜๊ณ , ์ ‘์ฐฉ์ œ๊ฐ€ ์ž˜ ๋ถ™๋„๋ก ๋„์™€์ค๋‹ˆ๋‹ค. ๋ฐ˜๋ฉด, ๊ฑด์‹๋ฒ•์€ ์ ‘์ฐฉ์ œ๋ฅผ ์‚ฌ์šฉํ•˜์ง€ ์•Š๊ณ , ํ‘œ๋ฉด์„ ๊ฑด์กฐ์‹œํ‚ค๊ณ  ์ ‘์ฐฉ์ œ๋ฅผ ๋ฐ”๋ฅด๋Š” ๋ฐฉ์‹์ž…๋‹ˆ๋‹ค. ์ด ๋ฐฉ๋ฒ•์€ ์ ‘์ฐฉ์ œ๋ฅผ ์‚ฌ์šฉํ•˜์ง€ ์•Š๊ธฐ ๋•Œ๋ฌธ์— ํ™˜๊ฒฝ์— ๋” ์•ˆ์ „ํ•˜๋ฉฐ, ์ž‘์—… ํ›„ ์ฒญ์†Œ๊ฐ€ ์šฉ์ดํ•ฉ๋‹ˆ๋‹ค. ๋‘ ๋ฐฉ๋ฒ• ๋ชจ๋‘ ๊ฐ๊ฐ์˜ ์žฅ๋‹จ์ ์ด ์žˆ์œผ๋ฉฐ, ์ž‘์—… ํ™˜๊ฒฝ๊ณผ ์š”๊ตฌ ์‚ฌํ•ญ์— ๋”ฐ๋ผ ์„ ํƒ๋ฉ๋‹ˆ๋‹ค.
๋กœํฌ์›ฐ ๊ฒฝ๋„์‹œํ—˜์—์„œ C ์Šค์ผ€์ผ ์‹œํ—˜๋ฒ•์„ ์„ค๋ช…ํ•˜์‹œ์˜ค. C ์Šค์ผ€์ผ ์‹œํ—˜๋ฒ•์€ Rockwell ๊ฒฝ๋„์‹œํ—˜๋ฒ• ์ค‘ ํ•˜๋‚˜๋กœ, ํ‘œ๋ฉด ๊ฒฝ๋„๋ฅผ ์ธก์ •ํ•˜๋Š” ๋ฐฉ๋ฒ•์ž…๋‹ˆ๋‹ค. C ์Šค์ผ€์ผ์€ ์ผ๋ฐ˜์ ์œผ๋กœ ํ•˜๋“œ๋ฉ”ํƒˆ, ๊ฐ•์ฒ , ์•Œ๋ฃจ๋ฏธ๋Š„, ํ”Œ๋ผ์Šคํ‹ฑ, ๊ณ ๋ฌด, ์œ ๋ฆฌ, ๊ธˆ์†, ๋น„๊ธˆ์†, ํ•ฉ๊ธˆ, ํ•ฉ์„ฑ์ˆ˜์ง€, ์œ ๋ฆฌ์„ฌ์œ , ์„ฌ์œ ๊ฐ•ํ™”ํ”Œ๋ผ์Šคํ‹ฑ, ์„ฌ์œ ๊ฐ•ํ™”์œ ๋ฆฌ, ์„ฌ์œ ๊ฐ•ํ™”์•Œ๋ฃจ๋ฏธ๋Š„, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌ์—์Šคํ„ฐ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌ์นด๋ณด๋„ค์ดํŠธ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌ์œ ๊ฐ•ํ™”ํด๋ฆฌํ”„๋กœํ•„๋ Œ, ์„ฌโš ๏ธ ๋กœํฌ์›ฐ ๊ฒฝ๋„์‹œํ—˜์€ ๊ธˆ์†์˜ ๊ฒฝ๋„๋ฅผ ์ธก์ •ํ•˜๋Š” ๋ฐฉ๋ฒ• ์ค‘ ํ•˜๋‚˜๋กœ, C ์Šค์ผ€์ผ ์‹œํ—˜๋ฒ•์€ ์ฃผ๋กœ ๊ฒฝํ™”๋œ ๊ธˆ์†์˜ ๊ฒฝ๋„๋ฅผ ์ธก์ •ํ•˜๋Š” ๋ฐ ์‚ฌ์šฉ๋ฉ๋‹ˆ๋‹ค. ์ด ์‹œํ—˜๋ฒ•์€ ์‹œํ—˜ ์‹œํŽธ์˜ ํ‘œ๋ฉด์„ ์—ฐ๋งˆํ•˜์—ฌ ๋งค๋„๋Ÿฝ๊ฒŒ ๋งŒ๋“  ํ›„, ๋กœํฌ์›ฐ ๊ฒฝ๋„๊ณ„์˜ ์••์ž๋กœ ์‹œํ—˜ํ•ฉ๋‹ˆ๋‹ค. ์••์ž๊ฐ€ ์‹œํ—˜ ์‹œํŽธ์— ์ ‘์ด‰ํ•  ๋•Œ, ์‹œํŽธ์ด ์••์ถ•๋˜๋ฉด์„œ ๊ฒฝ๋„๊ฐ€ ์ฆ๊ฐ€ํ•˜๊ฒŒ ๋ฉ๋‹ˆ๋‹ค. ์ด ๊ณผ์ •์—์„œ ์••์ž์˜ ํ•˜์ค‘์„ ์ฆ๊ฐ€์‹œํ‚ค๋ฉฐ, ์‹œํŽธ์˜ ๊ฒฝ๋„๊ฐ€ ๋ณ€ํ•˜๋Š” ๊ฒƒ์„ ๊ด€์ฐฐํ•ฉ๋‹ˆ๋‹ค. ๋กœํฌ์›ฐ ๊ฒฝ๋„์‹œํ—˜์€ ์ผ๋ฐ˜์ ์œผ๋กœ HRC 60 ์ •๋„ ์ด์ƒ์˜ ๊ฒฝ๋„๋ฅผ ๊ฐ€์ง„ ๊ธˆ์†์— ์ ํ•ฉํ•˜๋ฉฐ, ๊ฒฝ๋„๊ฐ’์€ ์‹œํ—˜ ์‹œํŽธ์˜ ๋‘๊ป˜์™€ ์žฌ๋ฃŒ์˜ ์ข…๋ฅ˜์— ๋”ฐ๋ผ ๋‹ฌ๋ผ์งˆ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
์™€์ด์–ด ์ปท ๊ฐ€๊ณต์—์„œ ๊ฐ€๊ณต์•ก์˜ ์—ญํ• ์— ๋Œ€ํ•˜์—ฌ ์„ค๋ช…ํ•˜์‹œ์˜ค. Wire EDM (Electrical Discharge Machining)์—์„œ ๊ฐ€๊ณต์•ก์€ ์ฃผ์š”ํ•œ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค. ์ฃผ๋กœ ์‚ฌ์šฉ๋˜๋Š” ๊ฐ€๊ณต์•ก์€ ๋ผ์ดํŠธ ์˜ค์ผ (Light Oil)๊ณผ ๊ฐ™์€ ๊ธฐ๋ฆ„ ๊ธฐ๋ฐ˜์˜ ๊ฐ€๊ณต์•ก์ž…๋‹ˆ๋‹ค. ์ด ๊ฐ€๊ณต์•ก์€ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค. ์™€์ด์–ด ์ปท ๊ฐ€๊ณต์—์„œ ๊ฐ€๊ณต์•ก์€ ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ์ค‘์š”ํ•œ ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•ฉ๋‹ˆ๋‹ค. ์ฒซ์งธ, ๊ฐ€๊ณต์•ก์€ ์ ˆ์—ฐ์ฒด๋กœ ์ž‘์šฉํ•˜์—ฌ ์ „๊ธฐ ๋ฐฉ์ „ ์‹œ ๋ฐœ์ƒํ•˜๋Š” ์ŠคํŒŒํฌ๋ฅผ ๋ฐฉ์ง€ํ•ฉ๋‹ˆ๋‹ค. ๋‘˜์งธ, ๊ฐ€๊ณต์•ก์€ ์—ด์„ ํก์ˆ˜ํ•˜์—ฌ ์™€์ด์–ด์™€ ๊ฐ€๊ณต ๋ถ€์œ„์˜ ์˜จ๋„๋ฅผ ๋‚ฎ์ถ”๋Š” ๋ฐ ๋„์›€์„ ์ค๋‹ˆ๋‹ค. ์…‹์งธ, ๊ฐ€๊ณต์•ก์€ ์™€์ด์–ด์™€ ๊ฐ€๊ณต ๋ถ€์œ„ ์‚ฌ์ด์˜ ๋งˆ์ฐฐ์„ ์ค„์—ฌ์ฃผ์–ด ๊ฐ€๊ณต ํšจ์œจ์„ ๋†’์ž…๋‹ˆ๋‹ค. ๋„ท์งธ, ๊ฐ€๊ณต์•ก์€ ์™€์ด์–ด์˜ ๋งˆ๋ชจ๋ฅผ ์ค„์ด๊ณ , ๊ฐ€๊ณต ํ’ˆ์งˆ์„ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ๋ฐ ๊ธฐ์—ฌํ•ฉ๋‹ˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๊ฐ€๊ณต์•ก์€ ์™€์ด์–ด์™€ ๊ฐ€๊ณต ๋ถ€์œ„์˜ ํ‘œ๋ฉด์„ ์ฒญ์†Œํ•˜์—ฌ ๊ฐ€๊ณต ํ’ˆ์งˆ์„ ์œ ์ง€ํ•˜๋Š” ๋ฐ ๋„์›€์„ ์ค๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์—ญํ•  ๋•๋ถ„์— ๊ฐ€๊ณต์•ก์€ ์™€์ด์–ด ์ปท ๊ฐ€๊ณต์—์„œ ๋งค์šฐ ์ค‘์š”ํ•œ ์š”์†Œ๋กœ ์ž‘์šฉํ•ฉ๋‹ˆ๋‹ค.

โš ๏ธ: max_new_token ๋„๋‹ฌ๋กœ ์ธํ•ด ์ข…๋ฃŒ

Quickstart

์•„๋ž˜ ์˜ˆ์‹œ ์ฝ”๋“œ๋ฅผ ํ™œ์šฉํ•˜๋ฉด Qwen2.5-GenX-7B-AWQ๋ฅผ transformers ๊ธฐ๋ฐ˜์œผ๋กœ ๋ถˆ๋Ÿฌ์™€ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers.generation import GenerationConfig
model_id = "INTERX/Qwen2.5-GenX-7B-AWQ"
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype="auto", trust_remote_code=True)
prompt = "์‚ฌ์ถœ์„ฑํ˜•์ด ๋ญ”๊ฐ€์š”?"
messages = [{"role": "user", "content": prompt}]
tokenized_chat = tokenizer.apply_chat_template(
        messages,
        tokenizer=True,
        add_generation_prompt=True,
        return_tensors='pt'
).to(model.device)
generated_ids = model.generate(tokenized_chat, max_new_tokens=512)
generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)

Citation

@misc{qwen2_5-genx-7b-awq,
    title = {Qwen2.5-GenX-7B-AWQ},
    url = {https://huggingface.co/INTERX/Qwen2.5-GenX-7B-AWQ/blob/main/README.md},
    author = {Gen.AI@INTERX},
    month = {May},
    year = {2025}
}
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