1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model = AutoModelForCausalLM.from_pretrained("durrif/seedy-v11")
4tokenizer = AutoTokenizer.from_pretrained("durrif/seedy-v11")
5
6messages = [
7 {"role": "system", "content": "Eres Seedy, el asistente IA de NeoFarm especializado en ganadería de precisión."},
8 {"role": "user", "content": "¿Cuáles son los requerimientos de lisina para cerdos en fase de cebo?"}
9]
10
11text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
12inputs = tokenizer(text, return_tensors="pt")
13outputs = model.generate(**inputs, max_new_tokens=512)
14print(tokenizer.decode(outputs[0], skip_special_tokens=True))
1@misc{seedy-v11-2026,
2 author = {Durrif, David},
3 title = {Seedy v11: NeoFarm AI for Precision Livestock},
4 year = {2026},
5 publisher = {NeoFarm},
6 url = {https://huggingface.co/durrif/seedy-v11}
7}