初始化项目，由ModelHub XC社区提供模型

Model: Oysiyl/qwen3-4b-unslop-good-lora-v1
Source: Original Platform

run_local_inference_new_sample_mac.py

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+from pathlib import Path
+import shutil
+import torch
+
+from huggingface_hub import hf_hub_download
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+REPO = 'Oysiyl/qwen3-4b-unslop-good-lora-v1'
+BASE = 'Qwen/Qwen3-4B'
+WORKDIR = Path('./local_inference_model_4b')
+PROMPT = (Path(__file__).resolve().parent / 'new_eval_sample.txt').read_text(encoding='utf-8').strip()
+
+WORKDIR.mkdir(parents=True, exist_ok=True)
+
+repo_files = [
+    'tokenizer.json',
+    'tokenizer_config.json',
+    'chat_template.jinja',
+]
+weight_files = [
+    'model-00001-of-00002.safetensors',
+    'model-00002-of-00002.safetensors',
+    'model.safetensors.index.json',
+]
+
+for fname in repo_files + weight_files:
+    src = hf_hub_download(repo_id=REPO, filename=fname)
+    shutil.copyfile(src, WORKDIR / fname)
+
+for fname in ['config.json', 'generation_config.json']:
+    src = hf_hub_download(repo_id=REPO, filename=fname)
+    shutil.copyfile(src, WORKDIR / fname)
+
+messages = [
+    {
+        'role': 'user',
+        'content': 'Polish this AI passage to feel more human while preserving meaning:\n' + PROMPT,
+    }
+]
+
+device = 'mps' if torch.backends.mps.is_available() else 'cpu'
+print(f'Using device: {device}')
+
+tokenizer = AutoTokenizer.from_pretrained(WORKDIR)
+model = AutoModelForCausalLM.from_pretrained(WORKDIR, torch_dtype='auto')
+model = model.to(device)
+
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors='pt').to(device)
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=400,
+    temperature=0.8,
+    repetition_penalty=1.1,
+    do_sample=True,
+)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))