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thisdudeabides/The-Sanitarium-Council-3B
The-Sanitarium-Council-3B is a text generation model from thisdudeabides. Use it when you need the model to write or continue text. It is set up for peft. The card lists the license as apache-2.0.
THIS MODEL IS FOR ENTERTAINMENT AND EDUCATIONAL PURPOSES ONLY. DO NOT use this model for actual medical advice, diagnosis, or treatment. The medical practices described by this model are from the 19th century and incl…
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From the Hugging Face model README
THIS MODEL IS FOR ENTERTAINMENT AND EDUCATIONAL PURPOSES ONLY.
DO NOT use this model for actual medical advice, diagnosis, or treatment. The medical practices described by this model are from the 19th century and include bloodletting, homeopathy, unproven herbal remedies, and other practices that are dangerous, debunked, and potentially fatal by modern medical standards.
If you have a medical concern, consult a licensed modern healthcare professional.
The Sanitarium Council 3B is a LoRA fine-tune of Meta's Llama-3.2-3B-Instruct that roleplays as a panel of 19th-century American medical "experts." It simulates the voices and beliefs of historical medical movements including Thomsonian herbalism, homeopathy, hydropathy (water cure), dietary moralism, and conventional Civil War-era medicine.
Think of it as a time machine to the worst doctor's office imaginable. You ask a medical question; a council of long-dead quacks argues about whether you need more leeches or a bread-only diet.
This is a parody. It is meant to be funny, absurd, and a window into how far medicine has come. Nothing this model says should be followed, trusted, or taken seriously.
The council draws from training data based on real historical texts by:
| Expert | Movement | Source Text |
|---|---|---|
| Sylvester Graham | Dietary Moralism | A Treatise on Bread, and Bread-making (1837) |
| Dr. John Harvey Kellogg | Hygienism | Ladies' Guide in Health and Disease |
| Samuel Hahnemann | Homeopathy | Organon of Medicine |
| Mary Gove Nichols | Hydropathy / Water Cure | Water Cure writings |
| Samuel Thomson | Herbalism | New Guide to Health |
| Civil War-era physicians | Conventional Medicine | Period medical advisers and surgical texts |
transformers, peft, torch, bitsandbytesimport torch
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
from peft import PeftModel
BASE_MODEL = "meta-llama/Llama-3.2-3B-Instruct"
ADAPTER = "thisdudeabides/The-Sanitarium-Council-3B"
# Load base model in 4-bit
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=torch.float16,
)
model = AutoModelForCausalLM.from_pretrained(
BASE_MODEL,
quantization_config=bnb_config,
device_map="auto",
)
# Load the LoRA adapter
model = PeftModel.from_pretrained(model, ADAPTER)
tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL)
# Format prompt (Alpaca style)
alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
### Instruction:
You are a 19th-century medical expert. Provide advice based on your era's medical knowledge.
### Input:
I have a headache. What should I do?
### Response:
"""
inputs = tokenizer(alpaca_prompt, return_tensors="pt").to("cuda")
with torch.no_grad():
outputs = model.generate(
**inputs,
max_new_tokens=256,
temperature=0.7,
do_sample=True,
pad_token_id=tokenizer.eos_token_id,
)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response.split("### Response:")[-1].strip())
| Parameter | Value |
|---|---|
| Base model | meta-llama/Llama-3.2-3B-Instruct |
| Method | LoRA (PEFT) + SFT (TRL) |
| LoRA rank | 16 |
| LoRA alpha | 16 |
| Target modules | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
| Quantization | 4-bit NF4 (bitsandbytes) |
| Training precision | FP16 |
| Batch size | 2 (with 4 gradient accumulation steps) |
| Learning rate | 2e-4 (linear decay) |
| Training steps | 120 |
| Max sequence length | 2048 |
| Final training loss | 2.54 |
| Hardware | NVIDIA GTX 1080 |
The model was fine-tuned on ~9 MB of instruction-output pairs generated from public domain 19th-century medical texts. The data was formatted in Alpaca style and augmented with synthetic dialogue examples to reinforce the historical personas.
This is a joke. This is not medicine. Do not eat only bread. Do not apply leeches. See a real doctor. Preferably one from this century.