content.raw: Forcefeeding masked T5-Small 1 billion human-association captions to fry it's brain. I really don't know how long it'll take until I start nor do I know the logistic challenges I'll face when moving data from A to B, but the outcome should completely fry it and make it only fixate on human and diffusion responses. Should be a fun experiment that can just kind of run on automation.
content.type: text
content.value: Forcefeeding masked T5-Small 1 billion human-association captions to fry it's brain. I really don't know how long it'll take until I start nor do I know the logistic challenges I'll face when moving data from A to B, but the outcome should completely fry it and make it only fixate on human and diffusion responses. Should be a fun experiment that can just kind of run on automation.
content.type: new_line
content.raw: The experiment's captions are available... mostly on my hf, I've had some rate limit problems that caused them to halt and I think I need to autogen another 100 million complex captions.
content.type: text
content.value: The experiment's captions are available... mostly on my hf, I've had some rate limit problems that caused them to halt and I think I need to autogen another 100 million complex captions.
content.type: new_line
content.raw: This WILL form heavy bias and burn-points. Random words will be peppered in the mix to allow the T5-Small to retain at least some semblance of what it was before I lobotomize it.
content.type: text
content.value: This WILL form heavy bias and burn-points. Random words will be peppered in the mix to allow the T5-Small to retain at least some semblance of what it was before I lobotomize it.
content.type: new_line
content.raw: Likely I'll completely freeze half and burn the other half for a couple million as a test point. See how it takes or if it dies before 50k or something and need a refined process.
content.type: text
content.value: Likely I'll completely freeze half and burn the other half for a couple million as a test point. See how it takes or if it dies before 50k or something and need a refined process.
content.type: new_line
content.raw: Oh great, even better. It didn't include the longer prompt variations. This won't start today.
content.type: text
content.value: Oh great, even better. It didn't include the longer prompt variations. This won't start today.
content.type: new_line
content.type: new_line
content.raw: Alright training began. I'm introducing a high degree variant of noise and chatter for the t5 to learn to bypass - while simultaneously increasing additional information output from the t5 in the process.
content.type: text
content.value: Alright training began. I'm introducing a high degree variant of noise and chatter for the t5 to learn to bypass - while simultaneously increasing additional information output from the t5 in the process.
content.type: new_line
content.raw: So far the outcome has been a degree of introduction for new information in the output. while simultaneously introducing rule of 3 parameterization into the T5 small.
content.type: text
content.value: So far the outcome has been a degree of introduction for new information in the output. while simultaneously introducing rule of 3 parameterization into the T5 small.
content.type: new_line
content.raw: I have high hopes.
content.type: text
content.value: I have high hopes.
rawContent: Forcefeeding masked T5-Small 1 billion human-association captions to fry it's brain. I really don't know how long it'll take until I start nor do I know the logistic challenges I'll face when moving data from A to B, but the outcome should completely fry it and make it only fixate on human and diffusion responses. Should be a fun experiment that can just kind of run on automation.
  The experiment's captions are available... mostly on my hf, I've had some rate limit problems that caused them to halt and I think I need to autogen another 100 million complex captions.
  This WILL form heavy bias and burn-points. Random words will be peppered in the mix to allow the T5-Small to retain at least some semblance of what it was before I lobotomize it.
  Likely I'll completely freeze half and burn the other half for a couple million as a test point. See how it takes or if it dies before 50k or something and need a refined process.
  Oh great, even better. It didn't include the longer prompt variations. This won't start today.
  
  Alright training began. I'm introducing a high degree variant of noise and chatter for the t5 to learn to bypass - while simultaneously increasing additional information output from the t5 in the process.
  So far the outcome has been a degree of introduction for new information in the output. while simultaneously introducing rule of 3 parameterization into the T5 small.
  I have high hopes.
reactions.reaction: 👀
reactions.users: John6666
commentators._id: 630cf55b15433862cfc9556f
commentators.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/630cf55b15433862cfc9556f/eCDA4WmWp546pY96cev9Q.jpeg
commentators.fullname: AbstractPhila
commentators.name: AbstractPhil
commentators.type: user