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from transformers import AutoTokenizer, AutoModelForCausalLM | |
import torch | |
def frase_a_semilla(frase): | |
semilla = "M" | |
if "Dom(Kin)" in frase: | |
semilla += "KKK" | |
if "Mot(NLS)" in frase: | |
semilla += "RRRR" | |
if "TF(GATA)" in frase: | |
semilla += "TFG" | |
if "*AcK@" in frase: | |
semilla += "AK" | |
return semilla | |
frase = input("🔤 Escribe tu frase GeneForgeLang: ") | |
semilla = frase_a_semilla(frase) | |
print("🧪 Semilla generada:", semilla) | |
tokenizer = AutoTokenizer.from_pretrained("nferruz/ProtGPT2", do_lower_case=False) | |
model = AutoModelForCausalLM.from_pretrained("nferruz/ProtGPT2") | |
inputs = tokenizer(semilla, return_tensors="pt") | |
with torch.no_grad(): | |
salida = model.generate( | |
inputs["input_ids"], | |
max_length=100, | |
do_sample=True, | |
top_k=50, | |
temperature=0.8, | |
num_return_sequences=1 | |
) | |
print("🧬 Proteína generada:") | |
print(tokenizer.decode(salida[0], skip_special_tokens=True)) |