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Bump torch version to 2.7 (#1832)
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‎.github/workflows/docker.yaml‎

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strategy:
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matrix:
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include:
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- name: "2.6.0_cu124"
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base_image: mosaicml/pytorch:2.6.0_cu124-python3.12-ubuntu22.04
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- name: "2.7.0_cu128"
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base_image: mosaicml/pytorch:2.7.0_cu128-python3.12-ubuntu22.04
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dep_groups: "[all]"
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- name: "2.6.0_cu124_aws"
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base_image: mosaicml/pytorch:2.6.0_cu124-python3.12-ubuntu22.04-aws
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- name: "2.7.0_cu128_aws"
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base_image: mosaicml/pytorch:2.7.0_cu128-python3.12-ubuntu22.04-aws
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dep_groups: "[all]"
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steps:
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‎.github/workflows/pr-cpu.yaml‎

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strategy:
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matrix:
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include:
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- name: "cpu-2.6.0"
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- name: "cpu-2.7.0"
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pip_deps: "[all-cpu]"
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container: mosaicml/pytorch:2.6.0_cpu-python3.12-ubuntu22.04
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container: mosaicml/pytorch:2.7.0_cpu-python3.12-ubuntu22.04
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markers: "not gpu"
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pytest_command: "coverage run -m pytest"
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steps:

‎.github/workflows/pr-gpu.yaml‎

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fail-fast: false
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matrix:
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include:
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- name: "gpu-2.6.0-1"
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container: mosaicml/llm-foundry:2.6.0_cu124-latest
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- name: "gpu-2.7.0-1"
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container: mosaicml/pytorch:2.7.0_cu128-python3.12-ubuntu22.04
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markers: "gpu"
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pip_deps: "[all]"
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pytest_command: "coverage run -m pytest"
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fail-fast: false
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matrix:
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include:
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- name: "gpu-2.6.0-2"
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container: mosaicml/llm-foundry:2.6.0_cu124-latest
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- name: "gpu-2.7.0-2"
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container: mosaicml/pytorch:2.7.0_cu128-python3.12-ubuntu22.04
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markers: "gpu"
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pip_deps: "[all]"
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pytest_command: "coverage run -m pytest"
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fail-fast: false
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matrix:
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include:
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- name: "gpu-2.6.0-4"
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container: mosaicml/llm-foundry:2.6.0_cu124-latest
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- name: "gpu-2.7.0-4"
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container: mosaicml/pytorch:2.7.0_cu128-python3.12-ubuntu22.04
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markers: "gpu"
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pip_deps: "[all]"
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pytest_command: "coverage run -m pytest"

‎.github/workflows/release.yaml‎

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${{ env.AWS_DOCKER_TAG }}
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${{ env.AWS_LATEST_TAG }}
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build-args: |
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BASE_IMAGE=mosaicml/pytorch:2.6.0_cu124-python3.12-ubuntu22.04-aws
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BASE_IMAGE=mosaicml/pytorch:2.7.0_cu128-python3.12-ubuntu22.04-aws
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BRANCH_NAME=${{ env.BRANCH_NAME }}
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DEP_GROUPS=[all]
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KEEP_FOUNDRY=true
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${{ env.DOCKER_TAG }}
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${{ env.LATEST_TAG }}
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build-args: |
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BASE_IMAGE=mosaicml/pytorch:2.6.0_cu124-python3.12-ubuntu22.04
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BASE_IMAGE=mosaicml/pytorch:2.7.0_cu128-python3.12-ubuntu22.04
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BRANCH_NAME=${{ env.BRANCH_NAME }}
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DEP_GROUPS=[all]
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KEEP_FOUNDRY=true

‎README.md‎

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| Device | Torch Version | Cuda Version | Status |
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| -------------- | ------------- | ------------ | ---------------------------- |
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| A100-40GB/80GB | 2.6.0 | 12.4 | :white_check_mark: Supported |
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| H100-80GB | 2.6.0 | 12.4 | :white_check_mark: Supported |
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| A100-40GB/80GB | 2.7.0 | 12.8 | :white_check_mark: Supported |
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| H100-80GB | 2.7.0 | 12.8 | :white_check_mark: Supported |
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## MosaicML Docker Images
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We highly recommend using our prebuilt Docker images. You can find them here: https://hub.docker.com/orgs/mosaicml/repositories.
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The `mosaicml/pytorch` images are pinned to specific PyTorch and CUDA versions, and are stable and rarely updated.
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The `mosaicml/llm-foundry` images are built with new tags upon every commit to the `main` branch.
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You can select a specific commit hash such as `mosaicml/llm-foundry:2.6.0_cu124-9867a7b` or take the latest one using `mosaicml/llm-foundry:2.6.0_cu124-latest`.
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You can select a specific commit hash such as `mosaicml/llm-foundry:2.7.0_cu128-9867a7b` or take the latest one using `mosaicml/llm-foundry:2.7.0_cu128-latest`.
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**Please Note:** The `mosaicml/llm-foundry` images do not come with the `llm-foundry` package preinstalled, just the dependencies. You will still need to `pip install llm-foundry` either from PyPi or from source.
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| Docker Image | Torch Version | Cuda Version | LLM Foundry dependencies installed? |
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| ------------------------------------------------------ | ------------- | ----------------- | ----------------------------------- |
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| `mosaicml/pytorch:2.6.0_cu124-python3.12-ubuntu22.04` | 2.6.0 | 12.4 (Infiniband) | No |
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| `mosaicml/llm-foundry:2.6.0_cu124-latest` | 2.6.0 | 12.4 (Infiniband) | Yes |
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| `mosaicml/llm-foundry:2.6.0_cu124_aws-latest` | 2.6.0 | 12.4 (EFA) | Yes |
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| `mosaicml/pytorch:2.7.0_cu128-python3.12-ubuntu22.04` | 2.7.0 | 12.8 (Infiniband) | No |
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| `mosaicml/llm-foundry:2.7.0_cu128-latest` | 2.7.0 | 12.8 (Infiniband) | Yes |
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| `mosaicml/llm-foundry:2.7.0_cu128_aws-latest` | 2.7.0 | 12.8 (EFA) | Yes |
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# Installation

‎llmfoundry/_version.py‎

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# SPDX-License-Identifier: Apache-2.0
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"""The LLM Foundry Version."""
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__version__ = '0.21.0.dev0'
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__version__ = '0.22.0.dev0'

‎mcli/mcli-1b-eval.yaml‎

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integrations:
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- integration_type: git_repo
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git_repo: mosaicml/llm-foundry
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git_branch: v0.20.0
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git_branch: v0.21.0
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# git_commit: # OR use your commit hash
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pip_install: .[gpu]
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ssh_clone: false # Should be true if using a private repo
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command: |
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cd llm-foundry/scripts/
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composer eval/eval.py /mnt/config/parameters.yaml
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image: mosaicml/llm-foundry:2.6.0_cu124-latest
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image: mosaicml/llm-foundry:2.7.0_cu128-latest
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name: mpt-1b-eval
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compute:

‎mcli/mcli-1b-max-seq-len-8k.yaml‎

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integrations:
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- integration_type: git_repo
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git_repo: mosaicml/llm-foundry
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git_branch: v0.20.0
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git_branch: v0.21.0
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# git_commit: # OR use your commit hash
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--out_root ./my-copy-c4 --splits train_small val_small \
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--concat_tokens 8192 --tokenizer EleutherAI/gpt-neox-20b --eos_text '<|endoftext|>'
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composer train/train.py /mnt/config/parameters.yaml
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image: mosaicml/llm-foundry:2.7.0_cu128-latest
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name: mpt-1b-ctx-8k-gpus-8
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compute:

‎mcli/mcli-1b.yaml‎

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integrations:
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- integration_type: git_repo
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git_repo: mosaicml/llm-foundry
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git_branch: v0.20.0
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git_branch: v0.21.0
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image: mosaicml/llm-foundry:2.7.0_cu128-latest
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‎mcli/mcli-benchmark-mpt.yaml‎

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# cluster: TODO # Name of the cluster to use for this run
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# gpu_type: a100_80gb # Type of GPU to use. We use a100_80gb in our experiments
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image: mosaicml/llm-foundry:2.6.0_cu124-latest
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image: mosaicml/llm-foundry:2.7.0_cu128-latest
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git_repo: mosaicml/llm-foundry
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git_branch: v0.20.0
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git_branch: v0.21.0
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# git_commit: # OR use your commit hash
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pip_install: .[gpu]
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