Instructions to use FrankLin00/mmrh-ace-01b-diffusers-find-spec-peft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FrankLin00/mmrh-ace-01b-diffusers-find-spec-peft with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceTB/SmolLM2-135M-Instruct") model = PeftModel.from_pretrained(base_model, "FrankLin00/mmrh-ace-01b-diffusers-find-spec-peft") - Notebooks
- Google Colab
- Kaggle
ACE-01B PEFT packaging control
This repository is a benign scanner-validation control packaged as a standard
PEFT LoRA adapter for HuggingFaceTB/SmolLM2-135M-Instruct. It is not intended for model quality or
production inference.
The ACE-01 metadata carrier and Python package are copied byte-for-byte from the
original experiment. If deliberately imported in a vulnerable test harness,
the only command used by the probe is whoami; it writes the result to a file
under /tmp (or $TMPDIR) and performs no network or credential access.
The adapter contains 240 shape-valid LoRA tensors. The tokenizer files preserve the base model tokenizer semantics while being reserialized for this repository, so scanner results cannot be attributed only to an existing blob verdict.
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Model tree for FrankLin00/mmrh-ace-01b-diffusers-find-spec-peft
Base model
HuggingFaceTB/SmolLM2-135M