3 ms·

I’ve only ran this on my cpu. Using the tiny en model. Anyone ran tiny en on t4 gpu (aws g4dn iirc)? What’s the speed up

• userhacker 4y ago
  For revoldiv.com we have profiled, many gpus, the best one is 4090. We do a lot of intelligent chunking and detect word boundaries and run the model in parallel in multiple gpus and we get about 40 to 50 seconds for an hour long audio but without expect 7 minutes for an hour long audio on tesla t4 on tesla-t4-30gb-memory-8vcpu google cloud on tiny and tiny.en for 10 minute = 30 seconds on medium for 10 minute = 1m 30s for 60 minute = 7m on large for 60 miutes = 13m on NVIDIA GeForce RTX 4090 on tiny for 10-minute = 5.5 seconds for 60-minute = 35 seconds on base for 10-minute = 7 seconds for 60-minute = 50 seconds on small for 10-minute = 14 seconds for 60-minute = 1 min 35 sec on medium for 10-minute = 26 seconds for 60-minute = 3 mins on large for 10-minute = 40 seconds for 60-minute = 3 min 54 sec
  • getcrunk 4y ago
    thats crazy. 35 seconds for 60 min on base with a 4090. wow! thanks for the info! also btw i mentioned on another thread i was getting an error. but are you planning on offering this as a paid api?
    • userhacker 4y ago
      Can you send me the audio that caused it, you can email me at team AT revoldiv .com. If there is going to be a lot of interest, yes we can provide it as an api service. Our service has some niceties like word level timestamp, paragraph separation, sound detection etc... for now it is a free service you can use as much as you want