初始化项目，由ModelHub XC社区提供模型

Model: CL-From-Nothing/Qwen3-4B-SSD-RLVE-Eval20-N20-global-step-500
Source: Original Platform

README.md

@@ -0,0 +1,36 @@
+---
+license: mit
+language:
+- en
+library_name: transformers
+pipeline_tag: text-generation
+base_model: Qwen/Qwen3-4B
+tags:
+- qwen3
+- ssd
+- self-distillation
+- rlve
+---
+
+# Qwen3-4B SSD (RLVE Eval20, N=20) — global step 500
+
+Weights merged from VERL FSDP SFT checkpoint **`global_step_500`** (500 optimizer steps, 1 epoch schedule) of
+**Simple Self-Distillation (SSD)** applied to **Qwen/Qwen3-4B**:
+sample N=20 self-generated responses from the frozen base model, then SFT on those samples.
+
+## Training data
+
+Parquet SFT corpus (16k rows, `messages` column):
+[CL-From-Nothing/RLVE-Eval20-Qwen3-4B-SSD-N20-SFT-Train](https://huggingface.co/datasets/CL-From-Nothing/RLVE-Eval20-Qwen3-4B-SSD-N20-SFT-Train).
+
+Companion 1.7B model: [CL-From-Nothing/Qwen3-1-7B-SSD-RLVE-Eval20-N20-global-step-500](https://huggingface.co/CL-From-Nothing/Qwen3-1-7B-SSD-RLVE-Eval20-N20-global-step-500).
+
+## Load
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "CL-From-Nothing/Qwen3-4B-SSD-RLVE-Eval20-N20-global-step-500"
+tok = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")
+```