Update README.md

README.md

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 [GGUF (Text-Only, not recommended)](https://huggingface.co/CausalLM/miniG/tree/gguf): There is a significant degradation, even with the F16.
 
+**Hint:** How can I check if my inference parameters and quantized inference are performing well? You can try having the model recite "The Gift of the Magi" by O. Henry (which is a public domain text). You should expect it to recite the entire text accurately, including the formatting.
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 A model trained on a synthesis dataset of over **120 million** entries, this dataset having been generated through the application of state-of-the-art language models utilizing large context windows, alongside methodologies akin to retrieval-augmented generation and knowledge graph integration, where the data synthesis is conducted within clusters derived from a curated pretraining corpus of 20 billion tokens, with subsequent validation performed by the model itself.
 
 Despite the absence of thorough alignment with human preferences, the model is under no obligation to cater to poorly constructed prompts or the clichés often found in conventional benchmarks. Bonus: Included is an implementation of a **Vision Language Model** that has undergone Locked-Image Tuning.
@@ -73,6 +75,8 @@ Despite the absence of thorough alignment with human preferences, the model is u
 
 [GGUF (纯文本，不推荐)](https://huggingface.co/CausalLM/miniG/tree/gguf): 即使使用F16，性能也有显著下降。
 
+***提示：** 如何检查我的推理参数和量化推理是否表现良好？你可以尝试让模型背诵朱自清的《背影》（这是一个公共领域的文本）。你应该期待它能够准确地背诵整个文本，包括格式和换行。
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 一个在超过**1.2亿**条数据合成数据集上训练的模型，这些数据集是通过应用具有大上下文窗口的最先进语言模型生成的，并结合了类似于检索增强生成和知识图谱集成的方法，数据合成是在一个由200亿个标记组成的预训练语料库中提取的聚类内进行的，随后由模型本身进行验证。
 
 尽管该模型没有完全对齐人类偏好，但它没有义务迎合不良构建的提示或常见基准测试中的陈词滥调。额外内容：包含了经过锁定图像微调的**视觉语言模型**实现。