initial commit

app.py

@@ -1,7 +1,51 @@
 import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import spaces
+from PIL import Image
+import io
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+models = {
+    "jinaai/reader-lm-0.5b": AutoModelForCausalLM.from_pretrained("jinaai/reader-lm-0.5b", trust_remote_code=True).to("cuda").eval(),
+}
+
+tokenizers = {
+    "jinaai/reader-lm-0.5b": AutoTokenizer.from_pretrained("jinaai/reader-lm-0.5b", trust_remote_code=True),
+}
+
+
+@spaces.GPU
+def run_example(html_content, model_id="jinaai/reader-lm-0.5b"):
+    model = models[model_id]
+    tokenizer = tokenizers[model_id]
+    messages = [{"role": "user", "content": html_content}]
+    input_text=tokenizer.apply_chat_template(messages, tokenize=False)
+    inputs = tokenizer.encode(input_text, return_tensors="pt").to(device)
+    outputs = model.generate(inputs, max_new_tokens=1024, temperature=0, do_sample=False, repetition_penalty=1.08)
+    return tokenizer.decode(outputs[0])
+
+
+css = """
+  #output {
+    height: 500px; 
+    overflow: auto; 
+    border: 1px solid #ccc; 
+  }
+"""
+
+with gr.Blocks(css=css) as demo:
+    gr.Markdown("""
+    # HTML-to-Markdown
+    """)
+    with gr.Tab(label="Main"):
+        with gr.Row():
+            with gr.Column():
+                model_selector = gr.Dropdown(choices=list(models.keys()), label="Model", value="maxiw/Florence-2-ScreenQA-base")
+                html_content = gr.Textbox(label="HTML")
+                submit_btn = gr.Button(value="Submit")
+            with gr.Column():
+                output_text = gr.Textbox(label="Markdown")
+
+        submit_btn.click(run_example, [html_content, model_selector], [output_text])
+
+demo.launch(debug=True)

requirements.txt

@@ -0,0 +1 @@
+transformers<=4.43.4