Reinforcement Learning
Transformers
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post-training
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agentic-coding
composer-2.5
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Instructions to use Codeseys/composer-replication-framework with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Codeseys/composer-replication-framework with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Codeseys/composer-replication-framework", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Baladithya Balamurugan
Wave 20: SageMaker GRPO smoke artifacts (F3) — runnable g5.2xlarge GSM8K
7453f13 | # Build + push the baked SageMaker RL image to this account's private ECR (F3 §3.2). | |
| # One-time (Admin). The one-shot smoke does NOT need this — use | |
| # python examples/gsm8k_grpo/run_sagemaker_launch.py --image dlc | |
| # which runs on the stock DLC + source_dir with no local build. Use this script | |
| # for the repeatable path (no per-job pip-install) and the DiLoCo N-replica | |
| # executor (which passes ContainerEntrypoint and wants the framework baked in). | |
| # | |
| # NOTE: the DLC base is GPU/linux-amd64 (~15 GB). On an Apple-Silicon host you | |
| # must cross-build: pass --platform linux/amd64 (set below). This is slow under | |
| # emulation; prefer building on a linux/amd64 host or CodeBuild for real use. | |
| set -euo pipefail | |
| REGION="${REGION:-us-west-2}" | |
| ACCOUNT="${ACCOUNT:-386931836011}" | |
| REPO="${REPO:-composer-rl}" | |
| TAG="${TAG:-smoke}" | |
| DLC_ACCOUNT="763104351884" | |
| REGISTRY="${ACCOUNT}.dkr.ecr.${REGION}.amazonaws.com" | |
| IMAGE="${REGISTRY}/${REPO}:${TAG}" | |
| REPO_ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" | |
| echo "[ecr] region=${REGION} image=${IMAGE}" | |
| # 1. Ensure the ECR repo exists (idempotent). | |
| aws ecr describe-repositories --repository-names "${REPO}" --region "${REGION}" >/dev/null 2>&1 \ | |
| || aws ecr create-repository --repository-name "${REPO}" --region "${REGION}" >/dev/null | |
| # 2. Log in to BOTH the DLC registry (to pull the base) and our own (to push). | |
| aws ecr get-login-password --region "${REGION}" \ | |
| | docker login --username AWS --password-stdin "${DLC_ACCOUNT}.dkr.ecr.${REGION}.amazonaws.com" | |
| aws ecr get-login-password --region "${REGION}" \ | |
| | docker login --username AWS --password-stdin "${REGISTRY}" | |
| # 3. Build (cross-arch on Apple Silicon) + push. | |
| docker build --platform linux/amd64 \ | |
| -f "${REPO_ROOT}/docker/Dockerfile.sagemaker" \ | |
| -t "${IMAGE}" "${REPO_ROOT}" | |
| docker push "${IMAGE}" | |
| echo "[ecr] pushed ${IMAGE}" | |
| echo "[ecr] launch with: python examples/gsm8k_grpo/run_sagemaker_launch.py --image ${IMAGE}" | |