Upload finetune_soc.py with huggingface_hub

finetune_soc.py

@@ -23,7 +23,7 @@ Loss is computed on ALL tokens so the model learns every participant's voice.
 import trackio
 from datasets import load_dataset
 from peft import LoraConfig
-from transformers import AutoTokenizer, BitsAndBytesConfig
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
 from trl import SFTConfig, SFTTrainer
 
 MODEL_ID = "swiss-ai/Apertus-8B-2509"
@@ -144,10 +144,17 @@ bnb_config = BitsAndBytesConfig(
     bnb_4bit_use_double_quant=True,
 )
 
+print("Loading model with 4-bit quantization (QLoRA)...")
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_ID,
+    quantization_config=bnb_config,
+    device_map="auto",
+)
+
 print("Initializing trainer...")
 trainer = SFTTrainer(
-    model=MODEL_ID,
-    model_init_kwargs={"quantization_config": bnb_config, "device_map": "auto"},
+    model=model,
+    processing_class=tokenizer,
     train_dataset=train_dataset,
     eval_dataset=eval_dataset,
     peft_config=peft_config,