初始化项目，由ModelHub XC社区提供模型

Model: diverWayne/mikky-64m
Source: Original Platform

README.md

@@ -0,0 +1,108 @@
+---
+language:
+- zh
+- en
+license: apache-2.0
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- text-generation
+- gguf
+- safetensors
+- minimind
+- llama-cpp
+- qwen3-compatible
+base_model: jingyaogong/minimind
+datasets:
+- jingyaogong/minimind_dataset
+---
+
+# mikky-64m
+
+**mikky-64m** is a 63,912,192-parameter small language model named **mikky**.
+It was trained by **HUANG JUNZHE 黄俊哲** with the `minimind-scratch` codebase, based on the MiniMind project/data format.
+
+This release is intended as a compact learning and experimentation checkpoint for local inference, model-format conversion, and small-model alignment workflows.
+
+## Training Line
+
+The released checkpoint uses the completed alignment path:
+
+`pretrain -> SFT -> mikky LoRA identity SFT -> DPO`
+
+GRPO was only run as a probe and is **not** used as the final release checkpoint.
+PPO was skipped because the local reward signal was not strong enough to justify another RL stage.
+
+## Identity
+
+The model identity/persona is:
+
+- Name: **mikky**
+- Trainer: **HUANG JUNZHE 黄俊哲**
+- Origin: a small-parameter model trained from this MiniMind-based scratch project
+
+## Files
+
+- `mikky-64m.pth`: native `minimind_scratch` state dict, BF16 tensors.
+- `model.safetensors`: Qwen3-compatible Hugging Face tensor names, BF16 tensors.
+- `mikky-64m-bf16.gguf`: llama.cpp GGUF export, BF16, not quantized.
+- `tokenizer.json`, `tokenizer_config.json`: MiniMind tokenizer files.
+- `config.json`, `generation_config.json`: Qwen3-compatible metadata used for conversion and loading.
+
+The final source checkpoint was `checkpoints/dpo_768_resume.pth`.
+
+## Prompt Format
+
+The training code uses MiniMind chat markers:
+
+```text
+<|im_start|>user
+你的问题<|im_end|>
+<|im_start|>assistant
+```
+
+## Native Usage
+
+Use the project code for native scratch inference:
+
+```bash
+python -m minimind_scratch.cli chat \
+  --weight out/hf/mikky-64m/mikky-64m.pth \
+  --prompt "请用一句话介绍你自己"
+```
+
+## llama.cpp / GGUF
+
+The GGUF file is BF16 and intentionally not quantized:
+
+```bash
+llama-cli -m mikky-64m-bf16.gguf \
+  -p "<|im_start|>user\n请用一句话介绍你自己<|im_end|>\n<|im_start|>assistant\n" \
+  -n 128
+```
+
+## Notes
+
+The GGUF export maps the scratch model to a Qwen3-compatible tensor layout because the model uses RMSNorm, SwiGLU MLP, grouped-query attention, RoPE, and q/k normalization.
+The GGUF structure and metadata were verified locally. Always verify generation quality in your target runtime before treating the GGUF file as production-ready.
+
+## Limitations
+
+- This is a very small model; expect limited reasoning, math, factual recall, and safety behavior.
+- It is not suitable for high-stakes medical, legal, financial, or safety-critical use.
+- GRPO/PPO are not part of the final release checkpoint.
+
+## Dataset And License
+
+This model was trained with the MiniMind small-data recipe from
+[`jingyaogong/minimind_dataset`](https://huggingface.co/datasets/jingyaogong/minimind_dataset).
+For this release, the dataset reference follows the MiniMind small dataset license: **Apache-2.0**.
+
+Main data files used by this run:
+
+- `pretrain_t2t_mini.jsonl`: pretraining data.
+- `sft_t2t_mini.jsonl`: supervised fine-tuning data.
+- `dpo.jsonl`: preference data for DPO.
+- `lora_identity_mikky.jsonl`: project-authored identity/persona data for mikky.
+
+The model card, exported native checkpoint, Safetensors checkpoint, and GGUF artifact are released under **Apache-2.0**.