Update app.py

app.py

@@ -16,6 +16,13 @@ import sklearn
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import accuracy_score, recall_score, precision_score, f1_score
 import pprint
+from peft import (
+    prepare_model_for_int8_training,
+    LoraConfig,
+    get_peft_model,
+    get_peft_model_state_dict,
+)
+
 
 
 #####################################################
@@ -97,6 +104,30 @@ tokenizer,model,device = load_tokenizer_and_model(base_model,  True)
 tokenizer,model,device = load_tokenizer_and_model_Blaize(base_model,  True)
 tokenizer.pad_token_id = 0
 
+#speziell für Blaize Model:
+TARGET_MODULES = [
+    "q_proj",
+    "k_proj",
+    "v_proj",
+    "down_proj",
+    "gate_proj",
+    "up_proj",
+]
+
+config = LoraConfig(
+    r=8,
+    lora_alpha=16,
+    target_modules=TARGET_MODULES,
+    lora_dropout=0.05,
+    bias="none",
+    task_type="CAUSAL_LM",
+)
+#config.save_pretrained(OUTPUT_DIR)
+model = get_peft_model(model, config)
+tokenizer.pad_token_id = 0
+
+
+
 ####################################################
 #Datensets für Finetuning laden
 dataset_neu = daten_laden("alexkueck/tis")