add howto

app.py

@@ -79,7 +79,50 @@ In addition to text tasks, 🙏🏻PLeIAs/📸📈✍🏻Florence-PDF also incor
 
 joinus = """🌟TeamTonic🌟 is always making cool demos! Join our active builder's 🛠️community 👻 [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/qdfnvSPcqP) On 🤗Huggingface:[MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to🌟 [Build Tonic](https://git.tonic-ai.com/contribute)🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
 """
+howto = """The advanced settings allow you to fine-tune the text generation process. Here's what each setting does and how to use it:
 
+### Top-k (Default: 50)
+Top-k sampling limits the next token selection to the k most likely tokens.
+
+- **Lower values** (e.g., 10) make the output more focused and deterministic.
+- **Higher values** (e.g., 100) allow for more diverse outputs.
+
+**Example:** For a creative writing task, try setting top-k to 80 for more varied language.
+
+### Top-p (Default: 1.0)
+Top-p (or nucleus) sampling selects from the smallest set of tokens whose cumulative probability exceeds p.
+
+- **Lower values** (e.g., 0.5) make the output more focused and coherent.
+- **Higher values** (e.g., 0.9) allow for more diverse and potentially creative outputs.
+
+**Example:** For a factual caption, set top-p to 0.7 to balance accuracy and creativity.
+
+### Repetition Penalty (Default: 1.0)
+This penalizes repetition in the generated text.
+
+- **Values closer to 1.0** have minimal effect on repetition.
+- **Higher values** (e.g., 1.5) more strongly discourage repetition.
+
+**Example:** If you notice repeated phrases, try increasing to 1.2 for more varied text.
+
+### Number of Beams (Default: 3)
+Beam search explores multiple possible sequences in parallel.
+
+- **Higher values** (e.g., 5) can lead to better quality but slower generation.
+- **Lower values** (e.g., 1) are faster but may produce lower quality results.
+
+**Example:** For complex tasks like dense captioning, try increasing to 5 beams.
+
+### Max Tokens (Default: 512)
+This sets the maximum length of the generated text.
+
+- **Lower values** (e.g., 100) for concise outputs.
+- **Higher values** (e.g., 1000) for more detailed descriptions.
+
+**Example:** For a detailed image description, set max tokens to 800 for a comprehensive output.
+
+Remember, these settings interact with each other, so experimenting with different combinations can lead to interesting results!
+"""
 device = "cuda" if torch.cuda.is_available() else "cpu"
 torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
 
@@ -131,7 +174,7 @@ def plot_bbox(image, data, use_quad_boxes=False):
             plt.text(x1, y1, label, color='white', fontsize=8, bbox=dict(facecolor='red', alpha=0.5))
 
     ax.axis('off')
-    
+
     return fig
 
 def draw_ocr_bboxes(image, prediction):
@@ -227,7 +270,7 @@ with gr.Blocks(title="Tonic's 🙏🏻PLeIAs/📸📈✍🏻Florence-PDF") as if
                 with gr.Group():
                     gr.Markdown(description)
         with gr.Row():
-            with gr.Accordion("Join Us", open=True):
+            with gr.Accordion("🫱🏻‍🫲🏻Join Us", open=True):
                 gr.Markdown(joinus)
         with gr.Row():
             with gr.Column(scale=1):
@@ -237,6 +280,8 @@ with gr.Blocks(title="Tonic's 🙏🏻PLeIAs/📸📈✍🏻Florence-PDF") as if
                     submit_button = gr.Button("📸📈✍🏻Process")
                     reset_button = gr.Button("♻️Reset")
                 with gr.Accordion("🧪Advanced Settings", open=False):
+                    with gr.Accordion("🏗️How To Use", open=True):
+                        gr.Markdown(how_to_use)                        
                     top_k = gr.Slider(minimum=1, maximum=100, value=50, step=1, label="Top-k")
                     top_p = gr.Slider(minimum=0.0, maximum=1.0, value=1.0, step=0.01, label="Top-p")
                     repetition_penalty = gr.Slider(minimum=1.0, maximum=2.0, value=1.0, step=0.01, label="Repetition Penalty")