Create app.py

app.py

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+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import gradio as gr
+
+MODEL_NAME = "manycore-research/SpatialLM-Llama-1B"
+
+# Carrega tokenizer e modelo
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME,
+    torch_dtype=torch.float16,
+    device_map="auto"  # Usa GPU se disponível
+)
+model.eval()
+
+# Função de geração
+def generate_response(prompt, temperature=0.7, top_p=0.95, max_new_tokens=200):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            do_sample=True,
+            temperature=temperature,
+            top_p=top_p,
+            max_new_tokens=max_new_tokens,
+            pad_token_id=tokenizer.eos_token_id
+        )
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Interface Gradio
+interface = gr.Interface(
+    fn=generate_response,
+    inputs=[
+        gr.Textbox(label="Prompt", placeholder="Digite algo como 'Luan invadiu a base da Hegemonia...'"),
+        gr.Slider(minimum=0.1, maximum=1.5, value=0.7, label="Temperature"),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, label="Top-p"),
+        gr.Slider(minimum=10, maximum=512, value=200, label="Max Tokens")
+    ],
+    outputs=gr.Textbox(label="Resposta do Modelo"),
+    title="SpatialLM - Llama 1B",
+    description="Modelo SpatialLM LLaMA 1B rodando com GPU no Hugging Face Spaces. Ideal pra geração de texto contextualizado e linguagem espacial. Use prompts criativos."
+)
+
+interface.launch()