Upload folder using huggingface_hub

README.md

@@ -34,8 +34,8 @@ Whether you are building an agent to query internal knowledge bases, control sma
 
 1.  **Clone the repository:**
     ```bash
-    hf download google/functiongemma-tuninglab --repo-type=space --local-dir=functiongemma-tuninglab
-    cd functiongemma-tuninglab
+    hf download google/functiongemma-tuning-lab --repo-type=space --local-dir=functiongemma-tuning-lab
+    cd functiongemma-tuning-lab
     ```
 
 2.  **Install dependencies:**

config.py

@@ -10,7 +10,7 @@ class AppConfig:
     """
     # Directory Setup
     ARTIFACTS_DIR: Final[Path] = Path("artifacts")
-    OUTPUT_DIR: Final[Path] = ARTIFACTS_DIR.joinpath("functiongemma-tuninglab-demo")
+    OUTPUT_DIR: Final[Path] = ARTIFACTS_DIR.joinpath("functiongemma-tuning-lab-demo")
     
     # Model & Data
     HF_TOKEN: Final[Optional[str]] = os.getenv('HF_TOKEN')

engine.py

@@ -403,7 +403,7 @@ class FunctionGemmaEngine:
                 token=oauth_token
             )
             tags = info.card_data.tags
-            tags.append("functiongemma-tuninglab")
+            tags.append("functiongemma-tuning-lab")
             metadata_update(repo_id, {"tags": tags}, overwrite=True, token=oauth_token)
 
             return f"✅ Success! Model uploaded to: {repo_url}"

ui.py

@@ -102,7 +102,7 @@ def _render_header():
     with gr.Column():
         gr.Markdown("# 🤖 FunctionGemma Tuning Lab: Fine-Tuning")
         gr.Markdown("Fine-tune FunctionGemma to understand your custom functions.<br>"
-                    "See [README](https://huggingface.co/spaces/google/functiongemma-tuninglab/blob/main/README.md) for more details.")
+                    "See [README](https://huggingface.co/spaces/google/functiongemma-tuning-lab/blob/main/README.md) for more details.")
         gr.Markdown("(Optional) Sign in to Hugging Face if you plan to push your fine-tuned model to the Hub later (3. Export).")
         with gr.Row():
             gr.LoginButton(value="Sign in with Hugging Face")
@@ -180,7 +180,7 @@ def _render_export_tab(engine_state, username_state):
                 gr.Markdown("#### Option B: Save to Hugging Face Hub")
                 gr.Markdown("Publish your fine-tuned model to your personal Hugging Face account.")
                 repo_name_input = gr.Textbox(
-                    label="Target Repository Name", value="functiongemma-270m-it-tuninglab", placeholder="e.g., functiongemma-270m-it-tuned", interactive=False
+                    label="Target Repository Name", value="functiongemma-270m-it-tuning-lab", placeholder="e.g., functiongemma-270m-it-tuned", interactive=False
                 )
                 push_to_hub_btn = gr.Button("Save to Hugging Face Hub", variant="secondary", interactive=False)
                 repo_id_preview = gr.Markdown("Target Repository: (Waiting for input...)")