Deploy TinyModel1 from GitHub Actions

README.md

@@ -14,13 +14,20 @@ tags:
 ---
 
 <div align="center">
-  <img src="TinyModel1Image.png" alt="TinyModel1" width="560" />
+  <img src="TinyModel1Image.png" alt="TinyModel1" style="max-width: 100%; width: 100%; height: auto; display: block;" />
 </div>
 
 # TinyModel1
 
 **TinyModel1** is a compact **encoder** model for **news topic classification**, trained from scratch on the [AG News](https://huggingface.co/datasets/fancyzhx/ag_news) dataset. It targets fast CPU/GPU inference, simple deployment behind a router or API, and use as a **baseline** before larger or domain-specific models.
 
+## Links
+
+- **Source code (train & export):** [https://github.com/HyperlinksSpace/TinyModel](https://github.com/HyperlinksSpace/TinyModel)
+- **This model on Hugging Face:** [HyperlinksSpace/TinyModel1](https://huggingface.co/HyperlinksSpace/TinyModel1)
+- **Live demo (Space):** [TinyModel1Space on the Hub](https://huggingface.co/spaces/HyperlinksSpace/TinyModel1Space) · [direct app](https://hyperlinksspace-tinymodel1space.hf.space)
+
+
 ---
 
 ## Model summary
@@ -65,8 +72,8 @@ This release fits a **small footprint** so you can run batch or interactive clas
 
 | Metric | Value |
 |:--|:--|
-| **Eval accuracy** | 0.5333 |
-| **Final train loss** | 1.1592 |
+| **Eval accuracy** | 0.5400 |
+| **Final train loss** | 1.1577 |
 
 Metrics are computed on the held-out eval split configured above; treat them as a **sanity-check baseline**, not a production SLA.
 

artifact.json

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     "Business",
     "Sci/Tech"
   ],
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+  "train_loss": 1.1577,
   "num_parameters": 1339268,
   "max_train_samples": 3000,
   "max_eval_samples": 600,

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