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Reflect Pete's pipeline DSL extensions in /compute/pipelines/ #879

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alfredoclarifai merged 1 commit into from
May 21, 2026
Merged

Reflect Pete's pipeline DSL extensions in /compute/pipelines/ #879

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12 changes: 12 additions & 0 deletions docs/compute/pipelines/README.mdx
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Expand Up @@ -89,6 +89,18 @@ The pipeline fine-tunes the model on a single-GPU instance (the template's compu

That's it — you have a fine-tuned model registered in your Clarifai model registry, ready to serve, evaluate, or refine further.

:::tip Python-first alternative

The LoRA template ships with both a YAML scaffold (`config.yaml`) and a Python DSL form (`dsl.py`). To upload directly from the DSL Python file instead of the scaffold:

```bash
clarifai pipeline upload dsl.py
```

Both paths produce the same pipeline. The DSL form is the recommended starting point if you plan to author your own custom pipelines — see the [Pipeline DSL reference](dsl-reference.md) for the full API (`@step`, `step_ref`, `>>` composition, `base_image`, etc.).

:::

### Customize Before Running

To override defaults at init time, pass `--set key=value` flags. For example, to fine-tune a different base model and change the number of epochs:
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2 changes: 2 additions & 0 deletions docs/compute/pipelines/dsl-reference.md
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Expand Up @@ -56,6 +56,8 @@ def prepare_text(input_text: str) -> str:
| `assets` | `list[str]` | Files or directories to bundle alongside the step's code. Paths are resolved relative to the source file containing the step. |
| `compute` | `ComputeInfo` | Compute resources for the step (CPU, memory, accelerators). See [Compute Requirements](#compute-requirements). |
| `python_version` | `str` | Python version to use inside the step's container. Defaults to `"3.12"`. |
| `base_image` | `Optional[str]` | Custom base Docker image for the step's container — e.g., a CUDA-enabled image for GPU steps. Defaults to Clarifai's standard base image. |
| `platform` | `Optional[str]` | Build platform for the step's container image (e.g., `"linux/amd64"`). Defaults to multi-architecture build. |
| `secrets` | `dict[str, str]` | Environment variable name → secret resource path. Secrets are mounted as environment variables at step runtime. |

### Step Input Parameters
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