llm_forge-25m

adesh01/llm_forge-25m

Llama-style transformer trained from scratch in JAX/Flax.

• Architecture: llama
• Target size: 25M parameters
• Layers: 4
• d_model: 512
• Heads: 8 Q / 4 KV (GQA repeat=2)
• d_ff: 1280
• Vocab: 32768 (BPE 32k)
• Max seq len: 1024
• RoPE theta: 10000.0
• Tied embeddings: True

Training

• Tokens trained: 1,280,049,152
• Steps: 9,766
• Final loss: 3.8750

Files

• params.safetensors — model weights (fp32)
• config.json — architecture (HF Llama format)
• tokenizer.json + tokenizer_config.json + special_tokens_map.json — 32k BPE
• generation_config.json — default sampling parameters

Usage (JAX/Flax, this repo)

from huggingface_hub import snapshot_download
from model.config import load_model_config
from model.lm import LM
from training.export import load_params_safetensors

path = snapshot_download("adesh01/llm_forge-25m")
cfg = load_model_config('model_25m')  # or load_model_config('model_<size>')
model = LM(config=cfg)
flat = load_params_safetensors(f'{path}/params.safetensors')