or nvm here ill let you in rn your good for this stuff of architecture
Banaxi PRO
Banaxi-Tech
AI & ML interests
SLMs, training from scratch, LoRA, TTS, Ternary models. AI Interpretability. BCI. Contact at banaxitech@gmail.com
Recent Activity
repliedto their post about 3 hours ago
hi everyone
we have released nacr
its not just any model, its nacr
we have 6 more features and this model only uses 20% of its total capacity!
check it out at https://huggingface.co/saicr/nacr
we're currently working on expanding access as we do more research but right now you have to use our gated access form
follow https://huggingface.co/saicr if you're interested
if you want to join saicr, first read the entire nacr readme, then press the join button.
repliedto their post about 3 hours ago
hi everyone
we have released nacr
its not just any model, its nacr
we have 6 more features and this model only uses 20% of its total capacity!
check it out at https://huggingface.co/saicr/nacr
we're currently working on expanding access as we do more research but right now you have to use our gated access form
follow https://huggingface.co/saicr if you're interested
if you want to join saicr, first read the entire nacr readme, then press the join button.
repliedto their post about 3 hours ago
hi everyone
we have released nacr
its not just any model, its nacr
we have 6 more features and this model only uses 20% of its total capacity!
check it out at https://huggingface.co/saicr/nacr
we're currently working on expanding access as we do more research but right now you have to use our gated access form
follow https://huggingface.co/saicr if you're interested
if you want to join saicr, first read the entire nacr readme, then press the join button.
Organizations
replied to their post about 3 hours ago
replied to their post about 3 hours ago
probrably soon after acr has released
replied to their post about 3 hours ago
we're gonna be cooking with nacr-1.1 which will be 1B parameters and ACR at 57M
replied to their post about 3 hours ago
You will be able to train any model, on any dataset, at any architecture.
replied to their post about 3 hours ago
Yeah guyslp
reacted to ereniko's post with โค๏ธโค๏ธ about 5 hours ago
Post
113
NEW CLAUDE HAIKU MODEL COMING
FINALLY AFTER A YEAR
ANTHROPIC ANNOUNCED HAIKU 5.5
FINALLY AFTER A YEAR
ANTHROPIC ANNOUNCED HAIKU 5.5
replied to their post about 6 hours ago
Uhm I could add support, its very early still rn
updated a
bucket about 10 hours ago
liked a
Space about 17 hours ago
reacted to their post with ๐คโค๏ธ๐๐๐ฅ about 18 hours ago
Post
626
We're excited to release BananaAll, our SLM Super App.
It allows you to do EVERYTHING you need to do to trains SLMs in a single app, no terminal, no 30 chrome tabs.
The train tab allows you to train models, select datasets from presets, and use other ones with auto mapping, model size slider, it automatically generates a training script for you.
Then after you've trained the model or want to compare it to competitors, the evaluation tab, run ARC EASY, ARC Challenge, Hellaswag, PIQA, Arithmark 3, BananaMind Base Bench and more! Simple Results screen.
And lastly the inference tab, run your trained models or others.
Normally you would need seperate apps or scripts for that, but the BananaAll Super App lets you do all of that in a single app.
We also trained a small 2.5M parameter model on 200M tokens of Fineweb edu, The results: BananaMind Base Bench 854 and 53% on PIQA. On only 200M tokens.
Check it out at https://github.com/BananaMind/BananaAll.
It allows you to do EVERYTHING you need to do to trains SLMs in a single app, no terminal, no 30 chrome tabs.
The train tab allows you to train models, select datasets from presets, and use other ones with auto mapping, model size slider, it automatically generates a training script for you.
Then after you've trained the model or want to compare it to competitors, the evaluation tab, run ARC EASY, ARC Challenge, Hellaswag, PIQA, Arithmark 3, BananaMind Base Bench and more! Simple Results screen.
And lastly the inference tab, run your trained models or others.
Normally you would need seperate apps or scripts for that, but the BananaAll Super App lets you do all of that in a single app.
We also trained a small 2.5M parameter model on 200M tokens of Fineweb edu, The results: BananaMind Base Bench 854 and 53% on PIQA. On only 200M tokens.
Check it out at https://github.com/BananaMind/BananaAll.
- 12 replies
posted an update about 19 hours ago
Post
626
We're excited to release BananaAll, our SLM Super App.
It allows you to do EVERYTHING you need to do to trains SLMs in a single app, no terminal, no 30 chrome tabs.
The train tab allows you to train models, select datasets from presets, and use other ones with auto mapping, model size slider, it automatically generates a training script for you.
Then after you've trained the model or want to compare it to competitors, the evaluation tab, run ARC EASY, ARC Challenge, Hellaswag, PIQA, Arithmark 3, BananaMind Base Bench and more! Simple Results screen.
And lastly the inference tab, run your trained models or others.
Normally you would need seperate apps or scripts for that, but the BananaAll Super App lets you do all of that in a single app.
We also trained a small 2.5M parameter model on 200M tokens of Fineweb edu, The results: BananaMind Base Bench 854 and 53% on PIQA. On only 200M tokens.
Check it out at https://github.com/BananaMind/BananaAll.
It allows you to do EVERYTHING you need to do to trains SLMs in a single app, no terminal, no 30 chrome tabs.
The train tab allows you to train models, select datasets from presets, and use other ones with auto mapping, model size slider, it automatically generates a training script for you.
Then after you've trained the model or want to compare it to competitors, the evaluation tab, run ARC EASY, ARC Challenge, Hellaswag, PIQA, Arithmark 3, BananaMind Base Bench and more! Simple Results screen.
And lastly the inference tab, run your trained models or others.
Normally you would need seperate apps or scripts for that, but the BananaAll Super App lets you do all of that in a single app.
We also trained a small 2.5M parameter model on 200M tokens of Fineweb edu, The results: BananaMind Base Bench 854 and 53% on PIQA. On only 200M tokens.
Check it out at https://github.com/BananaMind/BananaAll.
- 12 replies
why is this on HF
liked a
model about 20 hours ago
published a
model about 20 hours ago
updated a
model about 20 hours ago