Create app.py

app.py

@@ -0,0 +1,35 @@
+import solara as sol
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_name = "datificate/gpt2-small-spanish"
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+def predict_next_token(text):
+    inputs = tokenizer(text, return_tensors="pt")
+    outputs = model(**inputs)
+    next_token_logits = outputs.logits[:, -1, :]
+    next_token_probs = torch.softmax(next_token_logits, dim=-1)
+    top_k_probs, top_k_indices = torch.topk(next_token_probs, 10)
+    top_k_tokens = tokenizer.convert_ids_to_tokens(top_k_indices[0])
+    return list(zip(top_k_tokens, top_k_probs[0].tolist()))
+
+@sol.component
+def NextTokenPredictionApp():
+    text = sol.use_state("")
+    predictions = sol.use_state([])
+
+    def on_text_change(new_text):
+        text.set(new_text)
+        preds = predict_next_token(new_text)
+        predictions.set(preds)
+
+    sol.InputText(value=text.value, on_change=on_text_change, placeholder="Escribe algo en español...")
+
+    if predictions.value:
+        sol.Markdown("### Predicciones de tokens:")
+        for token, prob in predictions.value:
+            sol.Markdown(f"- {token}: {prob:.4f}")
+
+sol.run(NextTokenPredictionApp)