初始化项目，由ModelHub XC社区提供模型

Model: lino-levan/qwen3-1.7b-smoltalk
Source: Original Platform

README.md

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+---
+library_name: transformers
+base_model:
+- Qwen/Qwen3-1.7B-Base
+---
+
+# Qwen3 1.7B Smoltalk
+
+Qwen3 1.7B just SFT'd on [smoltalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk).
+
+Trained using TRL with:
+
+- 4x H100 from lambda labs
+- epochs: 2 (i.e. 3,300 steps using our batch size)
+- effective batch size: 128 (4 per gpu, 8 grad accumulation steps)
+- warmup ratio: 0.03
+- weight decay: 0.01
+- learning rate: Forgot, will come back to add later.
+- learning rate scheduler: cosine
+- final training loss: 0.6432
+
+
+|Benchmark|Score|
+|---------|-----|
+|AIME25|0%|
+|GPQA|24.8%|
+|GSM8K|54.2%|
+|IFBench|18.3%|
+|IFEval|55%|
+|MMLU-Pro|22.8%|
+|Multi-IF|32.5%|
+
+## Quick Start
+
+```python
+from transformers import pipeline
+
+pipe = pipeline(
+    "text-generation",
+    model="lino-levan/qwen-3-1.7b-smoltalk",
+)
+messages = [
+    {"role": "user", "content": "What is 3 * 8?"},
+]
+output = pipe(messages)
+print(output[0]["generated_text"][-1]["content"])
+```
+