inference.py

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "Evicka/Hanse2-100M-Base"
# model_id = "."  # Load from local directory

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
model.eval()

prompt = "Artificial intelligence is"
inputs = tokenizer(
    prompt,
    return_tensors="pt",
    return_token_type_ids=False,
).to(model.device)

with torch.inference_mode():
    output = model.generate(
        **inputs,
        max_new_tokens=150,
        do_sample=True,
        temperature=0.5,
        top_k=25,
        top_p=0.9,
        repetition_penalty=1.2,
    )

print(tokenizer.decode(output[0], skip_special_tokens=True))