Views
No views yet
| Field | Value |
|---|---|
| Parameters | 756,819,456 |
| Layers / hidden size | 24 / 1,536 |
| Attention heads | 12 (MHA) |
| FFN size | 4,096 (SwiGLU/SiLU) |
| Position encoding | RoPE, theta 10,000 |
| Normalization | RMSNorm |
| Embeddings | Tied |
| Tokenizer | GPT-2 BPE, vocabulary padded to 50,304 |
| Context | 2,048 tokens |
| Published weights | BF16 |
LlamaForCausalLM, but this is a from-scratch D24
model with the GPT-2 tokenizer, not a Llama-family pretrained checkpoint.4e-4, weight decay 0.1, gradient clip 1.0, and a WSD schedule with
845 warmup steps and a final 16,905-step cosine decay to 4e-5. Final held-out
language-model loss was 2.256648 (perplexity 9.551).1import torch
2from transformers import AutoModelForCausalLM, AutoTokenizer
3
4model_id = "sfanm/d24-v6-pretrain"
5tokenizer = AutoTokenizer.from_pretrained(model_id)
6model = AutoModelForCausalLM.from_pretrained(
7 model_id, dtype=torch.bfloat16, device_map="auto"
8)megatron/,
from iter_0004000 through the terminal iter_0084527 (including the
deadline checkpoint iter_0067040).