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Guardpoint: gemma-4-12B, Qwen3-14B, gpt-oss-20b, Qwen3.5-27B, Qwen3-32B, gpt-oss-120b
Guardpoint is a medical reasoning specialist built on Qwen 3.
- Finetuned on our high-difficulty medical reasoning data generated with Deepseek V3.2 Speciale!
- Structured medical reasoning: organized, informative responses for medical diagnosis, management, knowledge, and understanding!
- Cut token costs: organized, concise responses use less tokens for faster inference!
- Trained on a wide variety of medical disciplines, patient profiles, and question types!
Prompting Guide
Guardpoint delivers structured medical responses using the Qwen 3 prompt format.
Guardpoint is a reasoning finetune; we recommend enable_thinking=True for all chats.
Example inference script to get started:
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "ValiantLabs/Qwen3-32B-Guardpoint"
# load the tokenizer and the model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype="auto",
device_map="auto"
)
# prepare the model input
prompt = "A 60-year-old undergoes a Total Knee Arthroplasty (TKA). Post-operatively, they complain of a clunking sensation and instability when descending stairs. On exam, they have excessive posterior translation of the tibia at 90 degrees of flexion. The TKA used a Cruciate Retaining (CR) implant. Diagnosis is PCL incompetence or rupture. Explain why a CR implant relies on a functional PCL for femoral rollback and how converting to a Posterior Stabilized (PS) implant resolves this biomechanical failure."
#prompt = "I have that tube in my chest for dialysis while my arm heals. The dressing came off in the shower and the tube got tugged a bit. It didn't come out, but now there's this red cuff thing showing that used to be inside the skin. It’s sticking out about an inch. Can I just push it back in and tape it?"
#prompt = "In the workup of a tumor of unknown primary, a biopsy shows a poorly differentiated carcinoma. The IHC profile is: CK7+, CK20+, CDX2+, TTF-1 negative, PAX8 negative. Based on this cytokeratin and transcription factor profile, where is the most likely primary site of the malignancy?"
#prompt = "I have bad arthritis in my lower back and hips. I saw a chiropractor who said my 'pelvis is twisted' and wants to do high-velocity adjustments. My rheumatologist said absolutely not because of my 'osteophytes'. Who is right? I just want to walk without stiffness."
messages = [
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True,
enable_thinking=True # Switches between thinking and non-thinking modes. Default is True.
)
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
# conduct text completion
generated_ids = model.generate(
**model_inputs,
max_new_tokens=32768
)
output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
# parsing thinking content
try:
# rindex finding 151668 (</think>)
index = len(output_ids) - output_ids[::-1].index(151668)
except ValueError:
index = 0
thinking_content = tokenizer.decode(output_ids[:index], skip_special_tokens=True).strip("\n")
content = tokenizer.decode(output_ids[index:], skip_special_tokens=True).strip("\n")
print("thinking content:", thinking_content)
print("content:", content)
DISCLAIMER: Guardpoint is a medical reasoning finetune that is subject to the strengths and weaknesses of LLMs. A conversation with an LLM is not a substitute for a professional medical examination. Utilize Guardpoint responsibly.
Guardpoint is created by Valiant Labs.
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