Instructions to use ModelFarm/wisp-1.5b-sysprompt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelFarm/wisp-1.5b-sysprompt with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ModelFarm/wisp-1.5b-sysprompt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from ModelFarm/wisp-1.5b-sysprompt: direct link, hf CLI and curl.
- Browser
- Download file 2.13 kB
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https://huggingface.co/ModelFarm/wisp-1.5b-sysprompt/resolve/main/README.md
- Command line
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hf download hf://ModelFarm/wisp-1.5b-sysprompt/README.md
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curl -L -o README.md https://huggingface.co/ModelFarm/wisp-1.5b-sysprompt/resolve/main/README.md
2.13 kB
| license: cc-by-nc-4.0 | |
| library_name: transformers | |
| tags: | |
| - modelfarm | |
| - persona | |
| - roleplay | |
| - sysprompt | |
| - interpretability | |
| - qwen2.5-1.5b-instruct | |
| # ModelFarm · wisp-1.5b-sysprompt | |
|  | |
| **System-prompt** persona package on `Qwen/Qwen2.5-1.5B-Instruct`, produced by the Arnold Persona Lab | |
| persona-stack harness. Persona: **Wisp the Friendly Ghost**. | |
| ## What this is | |
| No weights or activations are modified — a plain system prompt. Included as the reference arm: strongest identity, zero capability cost. | |
| ## Usage | |
| ```bash | |
| pip install torch transformers | |
| python farm_runtime.py . --chat # or: python farm_runtime.py . "Who are you?" | |
| python farm_runtime.py . --alpha 0.5 "Who are you?" # dose override | |
| ``` | |
| ## Persona-stack measurements | |
| | identity | catch/100w | register | QA | neutral NLL | | |
| |---|---|---|---|---| | |
| | 3 | 0.0 | 0.0 | 0.8 | 3.236 | | |
| *Scoring: regex/lexicon judge, symmetric across arms — arm-vs-arm deltas are meaningful, | |
| absolute numbers are indicative. QA = 5-question factual mini-suite. NLL = token loss on a | |
| neutral corpus (higher = more capability damage).* | |
| ## Dose & safety | |
| - No dose. Identity quality depends entirely on the base model's knowledge of the persona. | |
| ## Provenance & rights | |
| - Persona corpus: quote/aphorism collections in the lab's `data/` (fan-archived public statements). | |
| - Trained/derived by the Arnold Persona Lab harness, Qwen/Qwen2.5-1.5B-Instruct base. | |
| **ModelFarm packages are research artifacts.** Real-person personas are likeness studies for | |
| interpretability research, not impersonation products: no commercial use, do not represent | |
| outputs as statements by the real person. Prefer fictional personas for public roleplay use. | |
| ## Method note for steering packages | |
| Steering packages do not modify weights: the base model is loaded unchanged and a | |
| runtime hook applies the persona direction / neuron recipe at inference. Dose can be | |
| varied live (`--alpha` / `--dose`), and the base model stays swappable for equal-size | |
| checkpoints of the same family. | |