SurjoLabs/Surjo-50m
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🏗️ Building on HF
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liked a model about 23 hours ago
SurjoLabs/Surjo-50m liked a model 1 day ago
fromziro/Sentimental-0.2M reacted to Banaxi-Tech's post with 🔥 4 days ago
We're going to release our BananaMind 2.1 models very soon!
We're also announcing 2 new models.
All of our models we will train are:
BananaMind 2.1 Flash Lite, 10M parameters with 8M in transformer and 2M in n-gram. 50B pretraining tokens.
BananaMind 2.1 Lite with 25M parameters, 5M in n-gram and 20M in transformer. 75B pretraining tokens.
BananaMind 2.1 Flash with 50M parameters, with undecided n-gram count yet. 100B pretraining tokens.
BananaMind 2.1 Pro with 145M parameters, with undecided n-gram count yet. 150-200B pretraining tokens.
BananaMind 2.1 Coder with 149M parameters with undecided n-gram count yet.
We're now announcing BananaMind 2.1 NanoCoder, a 10M parameter model focused specifically on coding and BananaMind 2.1 MiniCoder which is a 25M parameter model focused on coding.
Follow us:
https://huggingface.co/BananaMind
@Banaxi-Tech
@vovaRL
@DedeProGames
https://huggingface.co/bananamind-research-community
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liked a
model about 23 hours ago
liked a
model 1 day ago
reacted to Banaxi-Tech's post with 🔥 4 days ago
Post
2970
We're going to release our BananaMind 2.1 models very soon!
We're also announcing 2 new models.
All of our models we will train are:
BananaMind 2.1 Flash Lite, 10M parameters with 8M in transformer and 2M in n-gram. 50B pretraining tokens.
BananaMind 2.1 Lite with 25M parameters, 5M in n-gram and 20M in transformer. 75B pretraining tokens.
BananaMind 2.1 Flash with 50M parameters, with undecided n-gram count yet. 100B pretraining tokens.
BananaMind 2.1 Pro with 145M parameters, with undecided n-gram count yet. 150-200B pretraining tokens.
BananaMind 2.1 Coder with 149M parameters with undecided n-gram count yet.
We're now announcing BananaMind 2.1 NanoCoder, a 10M parameter model focused specifically on coding and BananaMind 2.1 MiniCoder which is a 25M parameter model focused on coding.
Follow us:
BananaMind
@Banaxi-Tech
@vovaRL
@DedeProGames
bananamind-research-community
We're also announcing 2 new models.
All of our models we will train are:
BananaMind 2.1 Flash Lite, 10M parameters with 8M in transformer and 2M in n-gram. 50B pretraining tokens.
BananaMind 2.1 Lite with 25M parameters, 5M in n-gram and 20M in transformer. 75B pretraining tokens.
BananaMind 2.1 Flash with 50M parameters, with undecided n-gram count yet. 100B pretraining tokens.
BananaMind 2.1 Pro with 145M parameters, with undecided n-gram count yet. 150-200B pretraining tokens.
BananaMind 2.1 Coder with 149M parameters with undecided n-gram count yet.
We're now announcing BananaMind 2.1 NanoCoder, a 10M parameter model focused specifically on coding and BananaMind 2.1 MiniCoder which is a 25M parameter model focused on coding.
Follow us:
@Banaxi-Tech
@vovaRL
@DedeProGames
- 5 replies
liked 2
models 4 days ago
liked 2
models 5 days ago
reacted to Banaxi-Tech's post with 🔥 6 days ago
Post
2884
We're excited to release BananaMind 2.1 Pico Preview!
It includes the first preview of our BananaMind 2.1 architecture!
This model gets near BananaMind 2 Micro performance at half the parameters and 37.5x less tokens!
Thats insane!
The current architectures includes about 500K parameters of the total 1.5M parameters in n-gram embeddings and the layer 2 is run twice.
It also includes XSA and the XSA refresh gate.
We're still going to improve the architecture in the final release.
Check it out at:
Follow us for more models:
BananaMind
@Banaxi-Tech
@vovaRL
@DedeProGames
It includes the first preview of our BananaMind 2.1 architecture!
This model gets near BananaMind 2 Micro performance at half the parameters and 37.5x less tokens!
Thats insane!
The current architectures includes about 500K parameters of the total 1.5M parameters in n-gram embeddings and the layer 2 is run twice.
It also includes XSA and the XSA refresh gate.
We're still going to improve the architecture in the final release.
Check it out at:
Follow us for more models:
@Banaxi-Tech
@vovaRL
@DedeProGames
- 3 replies
liked a
model 7 days ago
reacted to Hoglet-33's post with 🔥 7 days ago
Post
3284
Pebble 10M and Pebble 10M Chat are now released!
Both models use our Mamba/Transformer 3:1 hybrid architecture and were pretrained on 25 billion tokens.
Pebble 10M Chat was additionally fine-tuned on 250 million tokens of Smol-SmolTalk to improve its conversational capabilities.
You can find them here:
- basically-ai/Pebble-10M
- basically-ai/Pebble-10M-Chat
We hope you enjoy using them. The rest of the Pebble family will be released soon.
Follow for more:
@Hoglet-33
basically-ai
Both models use our Mamba/Transformer 3:1 hybrid architecture and were pretrained on 25 billion tokens.
Pebble 10M Chat was additionally fine-tuned on 250 million tokens of Smol-SmolTalk to improve its conversational capabilities.
You can find them here:
- basically-ai/Pebble-10M
- basically-ai/Pebble-10M-Chat
We hope you enjoy using them. The rest of the Pebble family will be released soon.
Follow for more:
@Hoglet-33
- 32 replies
reacted to Banaxi-Tech's post with 🚀 7 days ago
Post
3436
Introducing BananaMindOS 3.0
- Complete modern UI redesign
- Adds support for Qwen3.5 0.8B, LFM2.5 230M,350M, SmolLM2 360M, Gemma 3 270M.
- Adds Q7,Q6,Q5,Q3,Q1 quantization formats with a easy to use precision slider
- And more!
The new UI includes:
- New 1024×768 High Quality interface.
- Photographic QOI background.
- Transparent BananaMind, CPU, cube, mouse, and Send icons.
- Proper bitmap cursor.
- Rounded translucent panels and cards.
- Modern model-loading progress window.
- Redesigned inference screen with response and prompt panels.
- Localized redraws for the cursor, clicks, loading progress, and precision slider.
Notice: Qwen3.5 0.8B currently generates garbled text, it will be fixed tomorrow.
See it for yourself
Now Available at https://github.com/BananaMind/BananaMindOS
Prebuild ISOs coming soon!
(also press ? + G if you want to load try to load a 6MB RAM model on 5MB may break)
- Complete modern UI redesign
- Adds support for Qwen3.5 0.8B, LFM2.5 230M,350M, SmolLM2 360M, Gemma 3 270M.
- Adds Q7,Q6,Q5,Q3,Q1 quantization formats with a easy to use precision slider
- And more!
The new UI includes:
- New 1024×768 High Quality interface.
- Photographic QOI background.
- Transparent BananaMind, CPU, cube, mouse, and Send icons.
- Proper bitmap cursor.
- Rounded translucent panels and cards.
- Modern model-loading progress window.
- Redesigned inference screen with response and prompt panels.
- Localized redraws for the cursor, clicks, loading progress, and precision slider.
Notice: Qwen3.5 0.8B currently generates garbled text, it will be fixed tomorrow.
See it for yourself
Now Available at https://github.com/BananaMind/BananaMindOS
Prebuild ISOs coming soon!
(also press ? + G if you want to load try to load a 6MB RAM model on 5MB may break)
- 7 replies
liked a
model 8 days ago
reacted to appvoid's post with 🔥 8 days ago
Post
3290
Love how the small lm community is getting identity over time:
- Channel-Mixing
- XSA
- Three-tower
- Digit aware
- Loops
No one is doing the same! That's so cool.
- Channel-Mixing
- XSA
- Three-tower
- Digit aware
- Loops
No one is doing the same! That's so cool.
- 36 replies
reacted to Banaxi-Tech's post with ❤️ 8 days ago
Post
3504
We're delaying BananaMind 2.1!
When BananaMind 2.1 Lite was almost done, we benchmarked it and the results we're worse than BananaMind 2 Mini.
We're going to spend alot more time in research on tiny models and then scaling up our techniques to the actual BananaMind 2.1 models!
We're also announcing these new models:
BananaMind 2.1 Coder: A 149M instruction tuned coder model trained on 75B tokens + 10B tokens of stack-v3-train.
BananaMind 2.1 Pico: A 1M parameter model trained on 22B tokens of data.
We also may release BananaMind 2.1 Large with around 100M parameters depending on how much compute we have.
Please give us a follow!
BananaMind
@Banaxi-Tech
---
@vovaRL
@DedeProGames
When BananaMind 2.1 Lite was almost done, we benchmarked it and the results we're worse than BananaMind 2 Mini.
We're going to spend alot more time in research on tiny models and then scaling up our techniques to the actual BananaMind 2.1 models!
We're also announcing these new models:
BananaMind 2.1 Coder: A 149M instruction tuned coder model trained on 75B tokens + 10B tokens of stack-v3-train.
BananaMind 2.1 Pico: A 1M parameter model trained on 22B tokens of data.
We also may release BananaMind 2.1 Large with around 100M parameters depending on how much compute we have.
Please give us a follow!
@Banaxi-Tech
---
@vovaRL
@DedeProGames
- 7 replies
liked a
model 9 days ago
reacted to appvoid's post with 🔥 10 days ago
Post
2635
Nobody knows what is doing, when you train a model, you are experimenting to advance the frontier, so keep failing 🫵
- 17 replies
liked a
Space 11 days ago
liked a
dataset 11 days ago
reacted to Hoglet-33's post with 🔥 11 days ago
Post
3047
We are announcing the first generation of the Pebble model family!
These are the models we are releasing:
- Pebble 10M
- Pebble 25M
- Pebble 50M
Each model will use a Mamba-Transformer 3:1 hybrid architecture and will be pretrained on 25 billion tokens before IFT and SFT.
Depending on development time and resources, we may also release:
- Pebble 5M
- Pebble 75M
- Pebble 1M (possibly)
We hope you're excited and enjoy the models!
Follow for more:
@Hoglet-33
basically-ai
These are the models we are releasing:
- Pebble 10M
- Pebble 25M
- Pebble 50M
Each model will use a Mamba-Transformer 3:1 hybrid architecture and will be pretrained on 25 billion tokens before IFT and SFT.
Depending on development time and resources, we may also release:
- Pebble 5M
- Pebble 75M
- Pebble 1M (possibly)
We hope you're excited and enjoy the models!
Follow for more:
@Hoglet-33
- 7 replies
upvoted a collection 11 days ago