| ## Usage: | |
| ``` | |
| from transformers import pipeline | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| tokenizer = AutoTokenizer.from_pretrained("SummerSigh/Pythia410m-Instruct-SFT") | |
| generator = pipeline('text-generation', model = 'SummerSigh/Pythia410m-Instruct-SFT') | |
| inpopo = input("Text here: ") | |
| text = generator("<user>" + inpopo + "<user><kinrel>" , max_length = 200, do_sample=True, top_p = 0.7, temperature = 0.5, repetition_penalty = 1.2, pad_token_id=tokenizer.eos_token_id) | |
| generated_text = text[0]["generated_text"] | |
| parts = generated_text.split("<kinrel>") | |
| cropped_text = "<kinrel>".join(parts[:2]) + "<kinrel>" | |
| print(cropped_text) | |
| ``` |