MetalGPT-1

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

torch.manual_seed(42)

model_name = "nn-tech/MetalGPT-1"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype="bfloat16",
    device_map="auto",
)

prompt = (
    "Назови плюсы и минусы хлоридной и сульфатной технологии производства никеля."
)

messages = [
    {"role": "system", "content": "Ты специалист в области металлургии."},
    {"role": "user", "content": prompt},
]

text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True,
    # enable_thinking=False
)

model_inputs = tokenizer([text], return_tensors="pt").to(model.device)

generated_ids = model.generate(
    **model_inputs,
    max_new_tokens=2048,
)

# Обрезаем префикс промпта
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)