Instructions to use camstack/camstack-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use camstack/camstack-trainer with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("camstack/camstack-trainer", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
File size: 1,421 Bytes
ebeed67 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | # Tracked in camstack/server as hf/camstack-trainer/Dockerfile; edit it there, not on the Hub.
#
# The CamStack trainer image. Two builders read this file:
# - `docker build --platform linux/amd64 --build-arg TRAINER_REVISION=<sha> .` (any registry);
# - the hub's Modal provider, which builds it WITHOUT a build context:
# FROM becomes `images.fromRegistry(...)` and every other line one
# `dockerfileCommands` entry.
# So, load-bearing:
# - only FROM, ARG, ENV, RUN and WORKDIR — never COPY or ADD (there is no context);
# - one instruction per line, no backslash continuations (the hub splits on lines);
# - every pip version pinned; the trainer itself installed from this repository
# at TRAINER_REVISION (the hub passes the exact commit it was released with).
FROM pytorch/pytorch:2.13.0-cuda12.6-cudnn9-runtime
ARG TRAINER_REVISION=main
ENV PYTHONUNBUFFERED=1
ENV PIP_NO_CACHE_DIR=1
ENV TRAINER_REVISION=${TRAINER_REVISION}
ENV YOLO_CONFIG_DIR=/tmp/ultralytics
RUN apt-get update && apt-get install -y --no-install-recommends git libgl1 libglib2.0-0 && rm -rf /var/lib/apt/lists/*
RUN pip install "camstack-train[train,export] @ git+https://huggingface.co/camstack/camstack-trainer@${TRAINER_REVISION}"
RUN python -c "import camstack_train, ultralytics, openvino, nncf, coremltools; print('trainer', camstack_train.__version__)"
WORKDIR /app
CMD ["python", "-m", "camstack_train", "--help"]
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