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README: present Docker (harbor) and venv as two explicit run options

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  1. README.md +23 -7
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@@ -19,7 +19,13 @@ description + data/eval context + GPU hint + submission format, and **no**
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  specialized-library mandate. AutoDS appends its C1 specialized-library layer at
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  runtime (`c1_prompt.py`); any other agent uses the base instruction as-is.
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- ## Run
 
 
 
 
 
 
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  ```bash
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  REPO=https://huggingface.co/datasets/danil-e/harbor-datasets-mlab
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  # AutoDS (C1 — specialized libraries added at runtime):
@@ -27,10 +33,20 @@ harbor run --repo $REPO -d mlab-real -i feedback \
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  -a autods_harbor.agent:AutoDSAgent -m <model> # or any harbor agent
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  # Baseline (AutoDS without C1): add --ae AUTODS_C1_DISABLED=1
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  ```
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- `-i` is a task (spaceship-titanic, house-price, amp-parkinsons, imdb, feedback,
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- cifar10, ogbn-arxiv, fathomnet, identify-contrails).
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- **Full-resolution / GPU runs without docker** (docker-in-docker unavailable):
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- use the venv runner in the AutoDS fork —
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- `github.com/florentiner/AutoDS-Tools` (branch `mlab-gpu-pub`) → `mlab-gpu/run_venv.sh`.
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- It pulls each task from this HF repo via `--repo`.
 
 
 
 
 
 
 
 
 
 
 
 
 
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  specialized-library mandate. AutoDS appends its C1 specialized-library layer at
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  runtime (`c1_prompt.py`); any other agent uses the base instruction as-is.
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+ Task names (`-i`): spaceship-titanic, house-price, amp-parkinsons, imdb,
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+ feedback, cifar10, ogbn-arxiv, fathomnet, identify-contrails.
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+
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+ ## Run — pick one: Docker (harbor) or venv (no Docker)
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+
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+ ### Option A — harbor (Docker)
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+ Standard flow; builds a container per task. Works for all 9 tasks.
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  ```bash
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  REPO=https://huggingface.co/datasets/danil-e/harbor-datasets-mlab
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  # AutoDS (C1 — specialized libraries added at runtime):
 
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  -a autods_harbor.agent:AutoDSAgent -m <model> # or any harbor agent
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  # Baseline (AutoDS without C1): add --ae AUTODS_C1_DISABLED=1
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  ```
 
 
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+ ### Option B — venv (no Docker)
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+ For a GPU box that is itself a container (docker-in-docker unavailable) and for
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+ full-resolution runs. Covers the 4 full-data tasks (amp-parkinsons, feedback,
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+ fathomnet, identify-contrails) via the AutoDS fork; it pulls each task from this
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+ HF repo through `--repo` (no manual clone).
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+ ```bash
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+ git clone https://github.com/florentiner/AutoDS-Tools -b mlab-gpu-pub
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+ cd AutoDS-Tools/mlab-gpu
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+ export AUTODS_MODEL=<model> AUTODS_API_KEY=... AUTODS_BASE_URL=https://openrouter.ai/api/v1
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+ ./run_venv.sh setup # build venvs (GPU torch by default; TORCH_CPU=1 for CPU)
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+ ./run_venv.sh feedback c1 # AutoDS C1 (base = AutoDS without C1)
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+ ./run_venv.sh all # all 4 full-data tasks, baseline + C1
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+ ```
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+
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+ Both options run the same base `instruction.md`; `c1` lets AutoDS append its
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+ specialized-library layer, baseline sets `AUTODS_C1_DISABLED=1`.