Model Details
- Model name: CHEESE-14B
- Base model: Qwen/Qwen3-14B
- Architecture: Qwen3ForCausalLM
- Parameter scale: 14B
- Precision: bfloat16
- Format: Safetensors
- Context length: 40,960 tokens
- License: Apache 2.0, following the base model license
Intended Use
CHEESE-14B is intended for research and development in medical language modeling, with an emphasis on musculoskeletal care. It can be used for experiments in clinical text understanding, medical reasoning, and domain-specific instruction following.
The model is not a medical device. It should not be used for autonomous diagnosis, treatment decisions, triage, or clinical deployment without independent validation, regulatory review, and clinician oversight.
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "SII-JasperLi77/CHEESE-14B"
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype="auto",
device_map="auto",
trust_remote_code=True,
)
messages = [
{"role": "user", "content": "Summarize the key considerations for postoperative rehabilitation after musculoskeletal surgery."}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True,
)
inputs = tokenizer([text], return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Limitations
CHEESE-14B may produce incorrect, incomplete, or unsupported medical statements. It may also reflect biases and limitations from the base model and fine-tuning process. Outputs should be treated as research artifacts and reviewed by qualified professionals before any clinical interpretation.
Citation
If you use this model, please cite the Qwen3 technical report and the CHEESE/OrthoPilot work when available.