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# What does this PR do? - see https://github.com/meta-llama/llama-stack/pull/689 <img width="591" alt="image" src="https://github.com/user-attachments/assets/76946a67-7373-43b5-8a03-0ad201aa543b" /> - leaving `tools/builtin.py` to avoid conflicts ## Test Plan - see https://github.com/meta-llama/llama-stack/pull/689 ## Sources Please link relevant resources if necessary. ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Ran pre-commit to handle lint / formatting issues. - [ ] Read the [contributor guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md), Pull Request section? - [ ] Updated relevant documentation. - [ ] Wrote necessary unit or integration tests.
25 lines
859 B
Python
25 lines
859 B
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from typing import List
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from llama_stack.providers.datatypes import Api, InlineProviderSpec, ProviderSpec
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def available_providers() -> List[ProviderSpec]:
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return [
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InlineProviderSpec(
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api=Api.post_training,
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provider_type="inline::torchtune",
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pip_packages=["torch", "torchtune", "torchao", "numpy"],
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module="llama_stack.providers.inline.post_training.torchtune",
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config_class="llama_stack.providers.inline.post_training.torchtune.TorchtunePostTrainingConfig",
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api_dependencies=[
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Api.datasetio,
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Api.datasets,
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],
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),
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]
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