try another home

Dockerfile

@@ -2,7 +2,8 @@
 FROM pytorch/pytorch:2.7.0-cuda12.8-cudnn9-devel
 
 # Set working directory
-WORKDIR /usr/src/app
+ENV HOME=/usr/src/app
+WORKDIR $HOME
 
 # Install system dependencies, then clean up
 RUN apt-get update && \
@@ -21,10 +22,10 @@ RUN pip install --upgrade pip && \
 RUN install -m 755 sft.py /usr/local/bin/sft
 
 # Set environment variable for Hugging Face cache
-ENV HF_HOME=/usr/src/app/.cache/huggingface
+# ENV HF_HOME=/usr/src/app/.cache/huggingface
 
 # Make /usr/src/app/ a writable directory
-RUN chmod -R 777 /usr/src/app
+RUN chmod -R 777 $HOME
 
 # Expose the Gradio port
 EXPOSE 7860

sft.py

@@ -1,15 +1,24 @@
 #!/usr/bin/env python3
 import argparse
 import subprocess
+import os
 
 parser = argparse.ArgumentParser(description="Demo script for the model.")
 
 parser.add_argument("--model", type=str)
 parser.add_argument("--dataset", type=str)
 parser.add_argument("--flavor", type=str)
+parser.add_argument("--token", type=str)
 
+# Parse the command line arguments
 args = parser.parse_args()
-print(f"Model: {args.model}, Dataset: {args.dataset}, Flavor: {args.flavor}")
+
+# Get the config file based on the model and flavor
+config_file = f"configs/{args.model}_{args.flavor}.yaml"
+
+# Check if the config file exists
+if not os.path.exists(config_file):
+    raise RuntimeError(f"Training model {args.model} with flavor {args.flavor} is not supported.")
 
 # Run another Python script
-subprocess.run(["trl", "sft", "--config", "configs/Qwen3-4B-Base_a10g-small.yaml"])
+subprocess.run(["trl", "sft", "--config", config_file, "--dataset_name", args.dataset])