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Unsloth notebooks

Published, not hardware-testedjupyterTraining / fine-tune

Unsloth's fast LoRA/QLoRA fine-tuning in JupyterLab.

Needs 15 GiB VRAM · CUDA on NVIDIA

No GPU big enough is free right now.

New machines appear as hosts connect them.

No speed benchmarks yet, so we match on price.

Template details
Rating
No ratings yet
Runs
0
Min VRAM
16 GB
Backend
CUDA · NVIDIA GPUs
Version
unsloth-jupyter-v1.0.0
Image digest
6cc938b2fe7a…
Health check
SSH probe on the leased endpoint

Web UI on the leased HTTP endpoint, protected by the per-job credential; SSH as the tenant too. Upstream publishes date-stamped nightly tags only (core-nightly-2026.09.24). Thin AmpleRun wrapper (templates/images/workspace, variant nb-unsloth) over unsloth/unsloth:core-nightly-2026.09.24@sha256:82ca28836356f94c2ed4b041e2d0900aadfddb115d58ba63f6f7e22f92fad0a1 (digest verified 2026-09-26); NOT BUILT, so image_digest is a placeholder that can be neither published nor rented. Licence: Apache-2.0 (https://github.com/unslothai/unsloth/blob/main/LICENSE). Needs an NVIDIA driver that supports CUDA 12.8 or newer. Status: not hardware-tested.

We match GPUs on their measured runtime and dedicated VRAM. A hardware report doesn't qualify another vendor's backend.

#fine-tuning #unsloth #notebook

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