---
language:
  - en
license: mit
library_name: flux
tags:
  - julia
  - flux-jl
  - distillation
  - knowledge-distillation
  - llama-style
  - gqa
  - rope
  - rmsnorm
  - swiglu
  - bpe
  - philosophy
  - text-generation
pipeline_tag: text-generation
datasets:
  - LisaMegaWatts/philosophy-corpus
model-index:
  - name: JuliaGPTDistill
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          type: LisaMegaWatts/philosophy-corpus
          name: philosophy-corpus
        metrics:
          - type: loss
            value: 7.44
            name: Val Loss
            verified: false
---

# JuliaGPTDistill

A **~5M parameter** LLaMA-style student model distilled from [JuliaFluxGPT](https://huggingface.co/LisaMegaWatts/JuliaFluxGPT) (10M params). Uses knowledge distillation with temperature scaling to compress the teacher's knowledge into a smaller architecture.

## Architecture

| Parameter | Value |
|-----------|-------|
| Architecture | LLaMA-style (RMSNorm, SwiGLU, RoPE, GQA) |
| Embedding dim | 256 |
| Layers | 4 |
| Query heads | 4 |
| KV heads | 2 (GQA ratio 2:1) |
| Head dim | 64 |
| Context length | 256 tokens |
| Vocabulary | 2,000 (ByteLevel BPE) |
| Dropout | 0.1 |
| Weight tying | Yes |
| Framework | Julia + Flux.jl |

## Distillation Settings

| Parameter | Value |
|-----------|-------|
| Teacher model | [JuliaFluxGPT](https://huggingface.co/LisaMegaWatts/JuliaFluxGPT) (512d/8L/8Q/2KV) |
| KD temperature | 4.0 |
| KD alpha | 0.5 |
| Loss | 0.5 * CE + 0.5 * KL(teacher \|\| student) |

## Training

| | Value |
|---|---|
| Dataset | [philosophy-corpus](https://huggingface.co/datasets/LisaMegaWatts/philosophy-corpus) |
| Tokenizer | BPE (2,000 vocab, ByteLevel) |
| Training steps | 4,089 |
| Best val loss | 7.44 |
| Hardware | NVIDIA RTX 3060 12GB |

## Inference Settings

| Parameter | Value |
|-----------|-------|
| vocab_size | 2,000 |
| context_length | 256 |
| temperature | 0.8 |
| top_k | 40 |

**Note:** This model requires the same BPE tokenizer used by JuliaFluxGPT. No tokenizer file is included in this repo — use the tokenizer from [JuliaFluxGPT](https://huggingface.co/LisaMegaWatts/JuliaFluxGPT/blob/main/tokenizer.json).

## Checkpoint Format

JLD2 files containing:
- `model_state` — Flux model weights
- `hyperparams` — `Dict("n_embd"=>256, "n_layer"=>4, "n_head"=>4, "n_kv_head"=>2, "vocab_size"=>2000, "block_size"=>256, "dropout"=>0.1, "kd_temperature"=>4.0, "kd_alpha"=>0.5)`
- `step`, `best_val_loss`, `train_losses`, `val_losses`

## Files

| File | Description |
|------|-------------|
| `best_model.jld2` | Best validation loss checkpoint |
| `final_model.jld2` | Final training step checkpoint |
| `checkpoint_latest.jld2` | Latest periodic checkpoint |

## Provenance

- **Author**: LisaMegaWatts
- **Source code**: [DavinciDreams/JuliaGPT](https://github.com/DavinciDreams/JuliaGPT)
- **Teacher model**: [LisaMegaWatts/JuliaFluxGPT](https://huggingface.co/LisaMegaWatts/JuliaFluxGPT)

## License

MIT