初始化项目，由ModelHub XC社区提供模型

Model: DuckyBlender/diegogpt-v2-mlx-bf16
Source: Original Platform

README.md

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+---
+library_name: mlx
+license: apache-2.0
+license_link: https://huggingface.co/Qwen/Qwen3-0.6B/blob/main/LICENSE
+pipeline_tag: text-generation
+base_model: Qwen/Qwen3-0.6B-MLX-bf16
+tags:
+- mlx
+datasets:
+- DuckyBlender/diego-replies-dataset
+---
+
+# DuckyBlender/diegogpt-v2-mlx-bf16
+
+This model [DuckyBlender/diegogpt-v2-mlx-bf16](https://huggingface.co/DuckyBlender/diegogpt-v2-mlx-bf16) is a full fine-tune of [Qwen/Qwen3-0.6B-MLX-bf16](https://huggingface.co/Qwen/Qwen3-0.6B-MLX-bf16), trained on the complete set of public replies from a specific individual.
+
+Training was conducted using `mlx-lm` version **0.26.0**. It ran for 15 steps with a batch size of 16, completing in a few seconds on a MacBook Pro M1 Pro (8-core CPU, 16GB RAM). Peak memory usage was 8.3GB. The dataset contained 225 low-quality training pairs (240 lines trained total).
+
+Run with system prompt `/no_think` and the following generation parameters:
+- `--temp 0.7`
+- `--top-p 0.8`
+- `--top-k 20`
+- `--min-p 0`
+
+Example usage:
+
+```bash
+pip install mlx-lm
+````
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("DuckyBlender/diegogpt-v2-mlx-bf16")
+
+prompt = "are you red hat hacker?"
+
+if tokenizer.chat_template is not None:
+    messages = [
+        {"role": "user", "content": user_input}
+    ]
+    prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False, enable_thinking=False)
+else:
+    prompt = user_input
+
+sampler = make_sampler(temp=0.7, top_p=0.8, top_k=20, min_p=0)
+
+response = mlx_lm.generate(
+    model,
+    tokenizer,
+    prompt=prompt,
+    sampler=sampler,
+    verbose=True
+)
+```
+
+Or directly via CLI:
+
+```bash
+mlx_lm.generate \
+  --model "DuckyBlender/diegogpt-v2-mlx-bf16" \
+  --temp 0.7 \
+  --top-p 0.8 \
+  --top-k 20 \
+  --min-p 0 \
+  --system "/no_think" \
+  --prompt "are you red hat hacker?"
+```
+
+Model uses \~1.25GB RAM during inference.
+