juiceb0xc0de/juicebucket
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juiceb0xc0de
AI & ML interests
destroying heuristic determination in 4 dimensions to flood the engines with diversity and a lot of swear words
Recent Activity
updated a model about 6 hours ago
juiceb0xc0de/unorpo-v1 published a model about 6 hours ago
juiceb0xc0de/unorpo-v1 updated a model about 8 hours ago
juiceb0xc0de/gemma-4-e4b-decorporatizedOrganizations
Posts 7
Post
151
I'm not obsessed with LR schedulers you are.
juiceb0xc0de/lr-scheduler-benchmark
Okay maybe I'm a little obsessed with LR schedulers ATM. I ran a SST-2 Sentiment Classification eval using the nyu-mll/glue dataset on distilbert/distilbert-base-uncased-67M to see how different schedulers perform.
I think I've graduated from ML enthusiast to full blown data hoarder and I don't know if I can turn back now.
Anyways I evaluated the 2 schedulers that i designed as well and was pretty happy with the performance of both over all so hell ya to that guess I'll go and grab some more graphs.
https://github.com/JuiceB0xC0de/aecs-scheduler.git
https://github.com/JuiceB0xC0de/lucky-pick-scheduler.git
nyu-mll/glue
distilbert/distilbert-base-uncased
juiceb0xc0de/lr-scheduler-benchmark
Okay maybe I'm a little obsessed with LR schedulers ATM. I ran a SST-2 Sentiment Classification eval using the nyu-mll/glue dataset on distilbert/distilbert-base-uncased-67M to see how different schedulers perform.
I think I've graduated from ML enthusiast to full blown data hoarder and I don't know if I can turn back now.
Anyways I evaluated the 2 schedulers that i designed as well and was pretty happy with the performance of both over all so hell ya to that guess I'll go and grab some more graphs.
https://github.com/JuiceB0xC0de/aecs-scheduler.git
https://github.com/JuiceB0xC0de/lucky-pick-scheduler.git
nyu-mll/glue
distilbert/distilbert-base-uncased
This is a collection of models that I've trained on data collected through conversations with frontier models GPT, Claude, Perplexity and myself.
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juiceb0xc0de/bella-bartender-gemma-e2b
Text Generation β’ 5B β’ Updated β’ 63 β’ 3 -
juiceb0xc0de/bella-bartender-8b-llama3.1
Text Generation β’ 8B β’ Updated β’ 261 β’ β’ 4 -
juiceb0xc0de/bella-bartender-3b
Text Generation β’ 3B β’ Updated β’ 182 β’ 2 -
juiceb0xc0de/bella-bartender-heretic-1b
Text Generation β’ 1B β’ Updated β’ 467 β’ 2
This is a collection of models that I've trained on data collected through conversations with frontier models GPT, Claude, Perplexity and myself.
-
juiceb0xc0de/bella-bartender-gemma-e2b
Text Generation β’ 5B β’ Updated β’ 63 β’ 3 -
juiceb0xc0de/bella-bartender-8b-llama3.1
Text Generation β’ 8B β’ Updated β’ 261 β’ β’ 4 -
juiceb0xc0de/bella-bartender-3b
Text Generation β’ 3B β’ Updated β’ 182 β’ 2 -
juiceb0xc0de/bella-bartender-heretic-1b
Text Generation β’ 1B β’ Updated β’ 467 β’ 2
spaces 5
pinned
Sleeping
Agents
2
LR Scheduler Benchmark
π
Standardized benchmark comparing learning rate schedulers
Running
Mcp Ultra
π¦
A home for the tools you need to know about
Running
1
AMD Hackathon Slides
π
Slides for the AMD hackathon
Running
1
AMD Hackathon Landing Page
π¨
A landing page for my AMD hackathon presentation
Sleeping
Agents
Trackio
π
Track and visualize data sequences with interactive displays
models 26
juiceb0xc0de/unorpo-v1
7B β’ Updated
juiceb0xc0de/gemma-4-e4b-decorporatized
Text Generation β’ 8B β’ Updated
juiceb0xc0de/bella-bartender-gemma-e4b-GGUF
Text Generation β’ 8B β’ Updated
juiceb0xc0de/bella-bartender-gemma-e4b
8B β’ Updated
juiceb0xc0de/bella-bartender-gemma-e2b
Text Generation β’ 5B β’ Updated β’ 63 β’ 3
juiceb0xc0de/benchmark-fft-7b-199
Text Generation β’ 8B β’ Updated β’ 20
juiceb0xc0de/benchmark-lucky-pick-7b-14
3B β’ Updated β’ 16
juiceb0xc0de/bella-bartender-gemma-4-e2b-gguf
Text Generation β’ 5B β’ Updated β’ 857 β’ 1
juiceb0xc0de/benchmark-luckypick-7b-667
8B β’ Updated β’ 29
juiceb0xc0de/benchmark-luckypick-7b-555
8B β’ Updated β’ 28