new

app.py

@@ -5,13 +5,15 @@ from trl import SFTTrainer
 from transformers import TrainingArguments
 from datasets import load_dataset
 import gradio as gr
-
+from huggingface_hub import HfApi, SpaceHardware
 
 max_seq_length = 4096
 dtype = None
 load_in_4bit = True
 hf_token = os.getenv("Token")
 
+api = HfApi(token=hf_token)
+
 print("Starting model and tokenizer loading...")
 
 # Load the model and tokenizer
@@ -117,6 +119,7 @@ trainer = SFTTrainer(
         bf16=is_bfloat16_supported(),
         warmup_steps=5,
         logging_steps=10,
+        max_steps=626,
         optim="adamw_8bit",
         weight_decay=0.01,
         lr_scheduler_type="linear",
@@ -136,9 +139,21 @@ print("Model saved successfully.")
 
 print("Pushing the model to the hub...")
 model.push_to_hub_merged(
-    "CyberSentinel-16bit",
+    "CyberSentinel-16bit-initial",
     tokenizer,
     save_method="merged_16bit",
     token=True
 )
-print("Model pushed to hub successfully.")
+print("Model pushed to hub successfully.")
+
+api.pause_space(repo_id="dad1909/CyberCode")
+
+print("Model is pause as initial.")
+
+# api.duplicate_space(
+#     from_id="original_space_id",
+#     secrets=[
+#         {"key": "HF_TOKEN", "value": "hf_api_***"},
+#         # Add more secrets if needed
+#     ],
+# )