| from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig, QuantoConfig, GenerationConfig | |
| model = "/Users/Goekdeniz.Guelmez@computacenter.com/Library/CloudStorage/OneDrive-COMPUTACENTER/Desktop/MiniMax01Text-Dev" | |
| hf_config = AutoConfig.from_pretrained(model, trust_remote_code=True) | |
| tokenizer = AutoTokenizer.from_pretrained(model) | |
| prompt = "Hello!" | |
| messages = [ | |
| {"role": "system", "content": "You are a helpful assistant created by MiniMax based on MiniMax-Text-01 model."}, | |
| {"role": "user", "content": prompt}, | |
| ] | |
| text = tokenizer.apply_chat_template( | |
| messages, | |
| tokenize=False, | |
| add_generation_prompt=True | |
| ) | |
| model_inputs = tokenizer(text, return_tensors="pt") | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model, | |
| trust_remote_code=True | |
| ) | |
| generation_config = GenerationConfig( | |
| max_new_tokens=20, | |
| eos_token_id=200020, | |
| use_cache=True, | |
| ) | |
| generated_ids = model.generate(**model_inputs, generation_config=generation_config) | |
| generated_ids = [ | |
| output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) | |
| ] | |
| response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] | |
| print(response) |