GPT-OSS 20B - Miles

1. Model Introduction

GPT-OSS is OpenAI’s open-weight language model, designed for reasoning, agentic tasks, and developer use cases. miles supports the 20 B variant. Key highlights:

Configurable reasoning effort: low / medium / high reasoning effort selectable per request.
Full chain-of-thought: the reasoning trace is exposed and trainable.
MXFP4 native weights: the HF checkpoint ships in MXFP4 (post-trained) — the BF16 launcher uses mbridge to load HF directly.
Sink attention: requires --qkv-format bshd on the Megatron path, which precludes dynamic batch sizing.

2. Supported Variants

Model	HF ID
gpt-oss-20b	openai/gpt-oss-20b

3. Environment Setup

3.1 Download model + datasets

hf download openai/gpt-oss-20b --local-dir /root/models/gpt-oss-20b
hf download --repo-type dataset zhuzilin/dapo-math-17k --local-dir /root/datasets/dapo-math-17k

3.2 HF → Megatron `torch_dist` conversion

The launcher needs no convert_hf_to_torch_dist.py step: it loads the HF checkpoint directly via --megatron-to-hf-mode bridge (mbridge).

4. Launch

4.1 Quick start

# Megatron BF16 (1 node × 8 GPU)
cd /root/miles
python scripts/run_gpt_oss_20b.py

The checkpoint is read from --model-dir (default /root/models) and the dataset from --data-dir (default /root/datasets).

5. Recipe Configuration

5.1 Parallelism

Launcher	TP	PP	CP	EP	expert-TP	`micro-batch-size`	GPUs
`run_gpt_oss_20b.py` (Megatron)	8	1	1	8	1	1	8 (1 × 8)

--use-dynamic-batch-size is not used on the Megatron BF16 path — the in-source comment explains: --qkv-format bshd (required for sink attention with TE) is incompatible with dynamic batch size. Only --micro-batch-size 1 is set. --sequence-parallel is on (required for TP + EP).

5.2 Algorithm

The recipe uses GRPO with --eps-clip 0.2 --eps-clip-high 0.28 --entropy-coef 0.00 and --rm-type math. --use-kl-loss is not passed — bridge mode has no Megatron-format reference checkpoint to supply --ref-load, which KL loss would need.

5.3 Rollout & SGLang

--rollout-num-gpus-per-engine 4
--sglang-dtype bfloat16
--sglang-decode-log-interval 1000
--sglang-mem-fraction-static 0.70

5.4 Optimizer

The launcher enables CPU Adam (--optimizer-cpu-offload --overlap-cpu-optimizer-d2h-h2d --use-precision-aware-optimizer).

5.5 Notable quirks

Attention setup:

--attention-dropout 0.0
--hidden-dropout 0.0
--qkv-format bshd        # required for TE sink attention (SWA + learnable softmax offset)
--attention-backend fused

--qkv-format bshd is mandated by the sink-attention pattern; in turn it precludes --use-dynamic-batch-size. Don’t toggle either flag without the other. The launcher passes no --load, and no --save unless you ask for it: --save exports the bf16 HF checkpoint to <model-dir>/gpt-oss-20b-BF16 every 50 steps, which can then be fed back in as the --hf-checkpoint.

6. Pairs Well With

Low Precision RL

​1. Model Introduction

​2. Supported Variants

​3. Environment Setup

​3.1 Download model + datasets

​3.2 HF → Megatron torch_dist conversion

​4. Launch

​4.1 Quick start

​5. Recipe Configuration

​5.1 Parallelism

​5.2 Algorithm

​5.3 Rollout & SGLang

​5.4 Optimizer

​5.5 Notable quirks

​6. Pairs Well With