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devstral-s
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modal-upgr
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5b56cc18d5 | ||
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5c3ac90669 | ||
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353ba4e80b |
2
.github/workflows/tests.yml
vendored
2
.github/workflows/tests.yml
vendored
@@ -228,6 +228,7 @@ jobs:
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echo "AXOLOTL_ARGS=${{ matrix.axolotl_args}}" >> $GITHUB_ENV
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echo "AXOLOTL_EXTRAS=${{ matrix.axolotl_extras}}" >> $GITHUB_ENV
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echo "CUDA=${{ matrix.cuda }}" >> $GITHUB_ENV
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echo "MODAL_IMAGE_BUILDER_VERSION=2024.10" >> $GITHUB_ENV
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echo "N_GPUS=${{ matrix.num_gpus }}" >> $GITHUB_ENV
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- name: Run tests job on Modal
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run: |
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@@ -268,6 +269,7 @@ jobs:
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echo "AXOLOTL_ARGS=${{ matrix.axolotl_args}}" >> $GITHUB_ENV
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echo "AXOLOTL_EXTRAS=${{ matrix.axolotl_extras}}" >> $GITHUB_ENV
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echo "CUDA=${{ matrix.cuda }}" >> $GITHUB_ENV
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echo "MODAL_IMAGE_BUILDER_VERSION=2024.10" >> $GITHUB_ENV
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echo "N_GPUS=${{ matrix.num_gpus }}" >> $GITHUB_ENV
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- name: Run tests job on Modal
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run: |
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@@ -38,16 +38,12 @@ temp_dir = tempfile.mkdtemp()
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with open(pathlib.Path(temp_dir) / "Dockerfile", "w", encoding="utf-8") as f:
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f.write(dockerfile_contents)
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cicd_image = (
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Image.from_dockerfile(
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pathlib.Path(temp_dir) / "Dockerfile",
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context_mount=None,
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force_build=True,
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gpu="A10G",
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)
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.env(df_args)
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.pip_install("fastapi==0.110.0", "pydantic==2.6.3")
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)
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cicd_image = Image.from_dockerfile(
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pathlib.Path(temp_dir) / "Dockerfile",
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context_mount=None,
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force_build=True,
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gpu="A10G",
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).env(df_args)
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app = App("Axolotl CI/CD", secrets=[])
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@@ -23,4 +23,4 @@ Here's a simple example of a stepwise supervised dataset entry:
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],
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"labels": [true, false]
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}
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```
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```
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