import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen3-1.7B-Base", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("nix3s/CHSA_Model")
prompt = "{ \"patient_id\": \"string\", \"symptoms\": \"Patient de 45 ans, douleur thoracique irradiant vers le bras gauche, sueurs froides\", \"age\": 120, \"antecedents\": \"string\", \"constantes\": { \"fc\": 110, \"spo2\": 94, \"ta\": \"145/90\", \"temperature\": 37.2 }, \"langue\": \"fr\" }'"
image = pipe(prompt).images[0]CHSA_Model
- Prompt
- { "patient_id": "string", "symptoms": "Patient de 45 ans, douleur thoracique irradiant vers le bras gauche, sueurs froides", "age": 120, "antecedents": "string", "constantes": { "fc": 110, "spo2": 94, "ta": "145/90", "temperature": 37.2 }, "langue": "fr" }'
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