Deploy TinyModel1Space from GitHub Actions

README.md

@@ -1,12 +1,14 @@
 ---
 title: TinyModel1Space
-emoji: 👁
-colorFrom: indigo
-colorTo: gray
+emoji: 🤗
+colorFrom: blue
+colorTo: indigo
 sdk: gradio
-sdk_version: 6.12.0
+sdk_version: 5.49.1
 app_file: app.py
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# TinyModel1Space
+
+Interactive demo for `HyperlinksSpace/TinyModel1`.

app.py

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+import os
+import gradio as gr
+from transformers import pipeline
+
+MODEL_ID = "HyperlinksSpace/TinyModel1"
+SPACE_URL = "https://hyperlinksspace-tinymodel1space.hf.space"
+_clf = None
+
+
+def get_pipeline():
+    global _clf
+    if _clf is not None:
+        return _clf
+    token = os.getenv("HF_TOKEN")
+    kwargs = {}
+    if token:
+        kwargs["token"] = token
+    _clf = pipeline(
+        "text-classification",
+        model=MODEL_ID,
+        tokenizer=MODEL_ID,
+        top_k=None,
+        **kwargs,
+    )
+    return _clf
+
+
+def _prediction_list(batch_output):
+    # One batch item: either a single {label, score} dict or a list of them.
+    if not batch_output:
+        return []
+    first = batch_output[0]
+    if isinstance(first, dict):
+        return [first]
+    if isinstance(first, list):
+        return first
+    return []
+
+
+def predict(text):
+    text = (text or "").strip()
+    if not text:
+        return {}, "Please enter some text first."
+    try:
+        clf = get_pipeline()
+    except Exception as exc:
+        return {}, f"Model load failed for {MODEL_ID}: {exc}"
+    raw = clf(text, truncation=True, max_length=128)
+    preds = _prediction_list(raw)
+    if not preds:
+        return {}, "Empty model output (unexpected pipeline shape)."
+    preds = sorted(preds, key=lambda x: float(x["score"]), reverse=True)
+    return {item["label"]: float(item["score"]) for item in preds}, "OK"
+
+
+EXAMPLES = [
+    ["Apple reported strong quarterly revenue growth and raised guidance."],
+    ["The team won the championship after a dramatic overtime finish."],
+    ["Scientists announced a new breakthrough in battery technology."],
+    ["Leaders met to discuss tensions and trade policy in the region."],
+]
+
+with gr.Blocks(title="TinyModel1Space") as demo:
+    gr.Markdown("# TinyModel1Space")
+    gr.Markdown("Model: `HyperlinksSpace/TinyModel1`")
+    gr.Markdown("Public URL: [https://hyperlinksspace-tinymodel1space.hf.space](https://hyperlinksspace-tinymodel1space.hf.space)")
+    inp = gr.Textbox(lines=4, label="Input text", placeholder="Paste a news sentence here...")
+    out = gr.Label(num_top_classes=4, label="Predicted class probabilities")
+    status = gr.Textbox(label="Status", interactive=False)
+    run_btn = gr.Button("Run Inference", variant="primary")
+    run_btn.click(fn=predict, inputs=inp, outputs=[out, status])
+    inp.submit(fn=predict, inputs=inp, outputs=[out, status])
+    gr.Examples(examples=EXAMPLES, inputs=inp)
+
+if __name__ == "__main__":
+    print(f"Space URL: {SPACE_URL}")
+    demo.launch(ssr_mode=False)

requirements.txt

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+gradio
+transformers
+torch