--- datasets: - Open-Orca/OpenOrca language: - en library_name: transformers --- # Test task For model inference run following ```python from peft import PeftModel, PeftConfig from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig from peft import PeftModel seed_value = 42 torch.manual_seed(seed_value) torch.cuda.manual_seed_all(seed_value) model_name = "lmsys/vicuna-7b-v1.5" lora_name = 'AlexWortega/PaltaTest' tokenizer = LlamaTokenizer.from_pretrained(model_name, model_max_length=1024) tokenizer.pad_token = tokenizer.eos_token model = PeftModel.from_pretrained( model, lora_name, torch_dtype=torch.float16 ) model.eval() model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16 ).to('cpu') model = PeftModel.from_pretrained(model, path_adapter) model.to(device) model.eval() def process_output(i, o): """ Simple output processing """ if isinstance(o, list): return [seq.split('A:')[1] for seq in o] elif isinstance(o, str): return o.split('A:')[1] else: return "Unsupported data type. Please provide a list or a string." def generate_seqs(q, k=2): q = 'Q:'+ q + 'A:' tokens = tokenizer.encode(q, return_tensors='pt').to(device) g = model.generate(input_ids=tokens) generated_sequences = tokenizer.batch_decode(g, skip_special_tokens=True) return generated_sequences q = """Given a weather description in plain text, rewrite it in a different style ```The weather is sunny and the temperature is 20 degrees. The wind is blowing at 10 km/h. Citizens are advised to go out and enjoy the weather. The weather is expected to be sunny tomorrow. ``` And the following style: "Angry weatherman" """ s = generate_seqs(q=q) s = process_output(q,s) print(s[0])# ``` should output something like these """ Angry weatherman: "The weather is sunny and the temperature is 20 degrees. The wind is blowing at 10 km/h. Citizens are advised to stay indoors and avoid going out. The weather is expected to be sunny tomorrow. """