c64-ministral-3-8b-thinking-c64-reasoning-lora

import torch
from peft import PeftModel
from transformers import AutoTokenizer
from transformers.models.mistral3 import Mistral3ForConditionalGeneration

base_id = "mistralai/Ministral-3-8B-Reasoning-2512"
adapter_id = "ibitato/c64-ministral-3-8b-thinking-c64-reasoning-lora"

tokenizer = AutoTokenizer.from_pretrained(base_id, trust_remote_code=True)
base_model = Mistral3ForConditionalGeneration.from_pretrained(
    base_id,
    torch_dtype=torch.bfloat16,
    trust_remote_code=True,
)
model = PeftModel.from_pretrained(base_model, adapter_id)

prompt = "Explain the C64 SID chip in one concise paragraph."
inputs = tokenizer(prompt, return_tensors="pt")
with torch.no_grad():
    out = model.generate(**inputs, max_new_tokens=128)
print(tokenizer.decode(out[0], skip_special_tokens=True))