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Load models from huggingface instead of blob storage (#22)
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@@ -10,12 +10,12 @@ on: | |
jobs: | ||
pre-commit-ci: | ||
runs-on: ubuntu-latest | ||
env: | ||
env: | ||
SKIP: "check-lincc-frameworks-template-version,pytest-check,no-commit-to-branch,validate-pyproject,check-added-large-files,sphinx-build" | ||
steps: | ||
- uses: actions/checkout@v3 | ||
with: | ||
fetch-depth: 0 | ||
fetch-depth: 0 | ||
- name: Setup Dependencies | ||
uses: ./.github/actions/deps | ||
with: | ||
|
@@ -24,4 +24,4 @@ jobs: | |
with: | ||
extra_args: --from-ref ${{ github.event.pull_request.base.sha }} --to-ref ${{ github.event.pull_request.head.sha }} | ||
- uses: pre-commit-ci/[email protected] | ||
if: always() | ||
if: always() |
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@@ -17,7 +17,6 @@ permissions: | |
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jobs: | ||
deploy: | ||
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runs-on: ubuntu-latest | ||
permissions: | ||
id-token: write | ||
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@@ -147,4 +147,4 @@ _results/ | |
_html/ | ||
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# mlflow output | ||
mlruns/ | ||
mlruns/ |
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@@ -1,28 +1,30 @@ | ||
$schema: https://azuremlschemas.azureedge.net/latest/commandJob.schema.json | ||
command: > | ||
python -m autora.doc.pipelines.main generate | ||
--model-path ${{inputs.model_dir}}/llama-2-7b-chat-hf | ||
python -m autora.doc.pipelines.main generate | ||
--model-path ${{inputs.model_path}} | ||
--output ./outputs/output.txt | ||
--sys-id ${{inputs.sys_id}} | ||
--instruc-id ${{inputs.instruc_id}} | ||
--param temperature=${{inputs.temperature}} | ||
--param top_k=${{inputs.top_k}} | ||
--param top_p=${{inputs.top_p}} | ||
autora/doc/pipelines/main.py | ||
autora/doc/pipelines/main.py | ||
code: ../src | ||
inputs: | ||
model_dir: | ||
type: uri_folder | ||
path: azureml://datastores/workspaceblobstore/paths/base_models | ||
# Currently models are loading faster directly from HuggingFace vs Azure Blob Storage | ||
# model_dir: | ||
# type: uri_folder | ||
# path: azureml://datastores/workspaceblobstore/paths/base_models | ||
model_path: meta-llama/Llama-2-7b-chat-hf | ||
temperature: 0.7 | ||
top_p: 0.95 | ||
top_k: 40 | ||
sys_id: SYS_1 | ||
instruc_id: INSTR_SWEETP_1 | ||
environment: | ||
environment: | ||
image: mcr.microsoft.com/azureml/curated/acpt-pytorch-2.0-cuda11.7:21 | ||
conda_file: conda.yml | ||
display_name: autodoc_prediction | ||
compute: azureml:t4cluster | ||
experiment_name: prediction | ||
description: | | ||
description: | |
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@@ -1,3 +1,3 @@ | ||
mlruns/ | ||
.mypy_cache/ | ||
__pycache__/ | ||
__pycache__/ |