Create load_model.py

load_model.py

@@ -0,0 +1,14 @@
+#from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+
+#model = AutoModelForCausalLM.from_pretrained("bigscience/bloom-1b7")
+#tokenizer = AutoTokenizer.from_pretrained("bigscience/bloom-1b7")
+
+#pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, max_new_tokens=2048, repetition_penalty=1.2, temperature=0.4)
+
+from transformers import pipeline
+
+# Cargar el modelo preentrenado (Bloom o cualquier otro compatible)
+def load_pipeline():
+    return pipeline("text-generation", model="bigscience/bloom-560m")
+
+pipe = load_pipeline()