how to use this shit :

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

repo_id = "iko-01/iko_im3"

# ุจุฏู„ REPO_BASE ุจุงู„ู„ูŠ ุฏุฑู‘ุจุช ุนู„ูŠู‡ ุฃูˆู„ ู…ุฑุฉ (ู…ุซู„ุงู‹ gpt2 ุฃูˆ iko-01/iko-v5e-1)
base_repo = "iko-01/iko-v5e-1"  

tokenizer = AutoTokenizer.from_pretrained(base_repo)
model = AutoModelForCausalLM.from_pretrained(repo_id)
model.to("cpu")

def ask_model(question, max_new_tokens=1000):
    prompt = f"### User:\n{question.strip()}\n\n### Assistant:\n"
    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, padding=True, max_length=1024)
    with torch.no_grad():
        gen = model.generate(
            inputs.input_ids,
            attention_mask=inputs.attention_mask,
            max_new_tokens=max_new_tokens,
            do_sample=True,
            top_p=0.95,
            temperature=0.9,
            pad_token_id=tokenizer.pad_token_id,
            eos_token_id=tokenizer.eos_token_id,
        )
    out = tokenizer.decode(gen[0], skip_special_tokens=True)
    if "### Assistant:" in out:
        return out.split("### Assistant:")[-1].strip()
    return out

print(ask_model("what is API"))
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