A weird model trained on a Pi. This model is a standalone version; no need to download anything else. (Please participate in a survey on the Community tab! I want to see why you use my model!) PLEASE FOR THE LOVE OF GOD FOLLOW BananaMind
Training Details
| Category | Specification |
|---|---|
| Model Architecture | GPT‑2 (decoder‑only Transformer) |
| Total Parameters | 346,104 |
| Model Size (FP32) | 1.32 MB (1,387,072 bytes) |
Layers (n_layer) | 2 |
Embedding Dimension (n_embd) | 92 |
Attention Heads (n_head) | 2 |
Context Length (n_positions) | 1024 |
| Vocabulary Size | 502 (byte‑level BPE, tied embeddings) |
| Training Framework | Oobabooga TextGen WebUI (Transformers + PEFT) |
| Fine‑Tuning Method | LoRA (Target all linear layers) |
| LoRA Rank | 8 |
| LoRA Alpha | 16 |
| Optimizer | AdamW 8‑bit (adamw_bnb_8bit) |
| Learning Rate | 2e‑4 (linear scheduler, 20 warmup steps) |
| Batch Size | 4 |
| Training Dataset | Capybara ShareGPT (random subset, 1.36 MB, 1,453,408 bytes) |
| Dataset Format | JSON array with "text" field (flattened ShareGPT) |
| Training Epochs | 5 |
| Loss Target | Stopped at ~6.0 (plateaued due to parameter limit) |
| Hardware | Raspberry Pi 5, 8GB RAM, ARM Cortex‑A76 (CPU only) |
| Training Time | ~1 hour |
| Tokenizer | Custom byte‑level BPE (trained on dataset) |
| Tokenizer Special Tokens | [BOS], [EOS], [PAD], [UNK] |
| Note | This is a proof‑of‑concept model. It fits on a 3.5‑inch floppy disk and was trained from scratch on a Raspberry Pi. |
This thing still produces nonsense. Be warned. Chats should be formatted as:
### User:
<user prompt>
### Assistant:
<assistant response>
Cite as:
[Single Floppy 346K Merged](https://huggingface.co/NILKNARFGonzo/single-floppy-346k-base/) by [Nilky](https://huggingface.co/NILKNARFGonzo) is licenced under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)