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pico-30
Banaxi-Tech/pico-30
pico-30 is a text generation model from Banaxi-Tech. Use it when you need the model to write or continue text. It is set up for transformers.
This is the 30% checkpoint of a 900,002-parameter base causal language model. It is not instruction tuned.
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At a glance
- Task
- Text Generation
- Library
- transformers
- Model type
- bananamind2_pico
- Access
- Public
- Created
- Aug 12, 2026
- Updated
- Aug 12, 2026
- SHA
- 645124ae
Try a prompt
Model card
From the Hugging Face model README
BananaMind 2 Pico Test - 30%
This is the 30% checkpoint of a 900,002-parameter base causal language model. It is not instruction tuned.
Architecture
| Field | Value |
|---|---|
| Parameters | 900,002 |
| Layers / hidden size | 6 / 96 |
| SwiGLU intermediate size | 380 |
| Query / KV heads | 6 / 2 |
| Head dimension | 16 |
| Context | 4,096 |
| Vocabulary | 384, tied |
| Refresh layers | 4 and 6 |
| Refresh kernel | Causal depthwise, width 9 |
The selective XSA refresh gate reads detached attention output as its signal, reinjects the original input embedding as its value, and carries convolution history alongside the K/V cache. Its learned residual scalar starts at zero.
Training
| Field | Value |
|---|---|
| Progress | 30% |
| Tokens seen | 60,001,615,872 |
| Target tokens | 200,000,000,000 |
| Hardware | 4 x NVIDIA H200 |
| Matrix optimizer | Stock torch.optim.Muon |
| Muon peak LR | 0.07 |
| Embedding/control optimizer | AdamW, LR 0.004 |
| Precision | bfloat16 autocast |
| Token range | FineWeb-HQ | Cosmopedia v2 |
|---|---|---|
| 0.00B-100.00B | 80% | 20% |
| 100.00B-200.00B | 60% | 40% |
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "Banaxi-Tech/pico-test"
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)
- Task
- Text Generation
- Library
- transformers
- Type
- bananamind2_pico
- Languages
- en
- Created
- Aug 12, 2026
- Updated
- Aug 12, 2026