初始化项目，由ModelHub XC社区提供模型

Model: Ashed00/SmolMath-135M Source: Original Platform
2026-05-26 23:27:57 +08:00
commit 7a3cc858d5
10 changed files with 294245 additions and 0 deletions
--- a/README.md
+++ b/README.md
@@ -0,0 +1,81 @@
+---
+library_name: transformers
+license: apache-2.0
+datasets:
+- Ashed00/combined_math_problems
+- openai/gsm8k
+- deepmind/aqua_rat
+base_model:
+- HuggingFaceTB/SmolLM2-135M
+---
+
+# SmolMath-135M
+
+SmolMath is a full finetuned version of SmolLM2-135M parameter, trained to obtain the highest math accuracy, with least drop in other text benchmarks.
+
+**Important**: All training codes are present in the [Github](https://github.com/Ashu-00/SmolMath/)
+**Important**: Please refer to the [Blog](https://hackmd.io/@ashu-00/SmolMath) for methodology and Training details.
+
+## Usage
+
+```python
+model_path = "Ashed00/SmolMath-135M"                                                                                                                                                                                                                                                                                                # Path where your fine-tuned model is saved
+from transformers import pipeline
+
+pipe = pipeline("text-generation", model=model_path)
+
+question = "What is 2+2?"
+
+prompt = "Question: " + question + "\nAnswer:"
+
+output = pipe(
+    prompt,
+    max_length=100,
+    do_sample=False,  # disable sampling for greedy decoding
+)[0]["generated_text"]
+
+
+```
+
+## Evaluation and Performance
+
+### Comparision with Base Model
+| **Metrics**       | **SmolLM2-135M-8k** | **SmolMath-135M** | **Δ (Change)** |
+|-------------------|---------------------|--------------------|----------------|
+| HellaSwag         | 42.1                | 41.15              | −0.95          |
+| PIQA              | 68.4                | 63.55              | −4.85          |
+| CommonsenseQA     | 33.9                | 33.42              | −0.48          |
+| TriviaQA          | 4.1                 | 0.0                | −4.10          |
+| Winogrande        | 51.3                | 51.78              | +0.48          |
+| OpenBookQA        | 34.6                | 30.80              | −3.80          |
+| GSM8K (0-shot)*    | 0.0                 | 6.9                | +6.90          |
+
+
+*This was evaluated using the lighteval script, which is favoured by the SmolLM2 creators in their evaluation and varies from the SmolMath prompt structure.
+
+### Math Benchmarks 
+    
+| Model                 | AddSub* (%) | MAWPS** (%) | GSM8K* (%) |
+|----------------------|------------|-----------|-----------|
+| apple/OpenELM-270M-Instruct | 2.14       | 2.83      |         2.05  |
+| HuggingFaceTB/SmolLM2-135M-Instruct      | 1.52       |4.04      |   0.45        |
+| SmolMath-no GRPO (ours)     | 9.64       | 7.47      |  6.22         |
+| SmolMath (ours)             | **12.05**  | **8.31**  |       **7.51**    |
+
+*Evaluated only on the test set, not included in the training
+**Evaluated on complete dataset, not included in the training
+
+## Citation
+
+Incase you want to use this model in your work, you can site us.
+
+```
+@misc{SmolMath,
+    title = {Building SmolMath: A Math Reasoning SLM Under 150M Parameters},
+    url = {https://hackmd.io/@ashu-00/SmolMath},
+    author = {ashu-00},
+    month = {July},
+    year = {2025}
+}
+
+```