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README.md

@@ -1,13 +1,17 @@
 ---
-title: Fable Traces
-emoji: 👀
-colorFrom: pink
-colorTo: purple
+title: fable-traces
+emoji: 📖
+colorFrom: red
+colorTo: gray
 sdk: gradio
 sdk_version: 6.19.0
-python_version: '3.12'
 app_file: app.py
-pinned: false
+short_description: Chat with fable-traces, a Qwen3-4B-Instruct finetune
+python_version: "3.12"
+startup_duration_timeout: 30m
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# fable-traces
+
+A streaming chat demo for [`AliesTaha/fable-traces`](https://huggingface.co/AliesTaha/fable-traces),
+a compact instruction-tuned model built on **Qwen3-4B-Instruct-2507**. Runs on ZeroGPU.

app.py

@@ -0,0 +1,133 @@
+import spaces
+import torch
+import gradio as gr
+from threading import Thread
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
+
+MODEL_ID = "AliesTaha/fable-traces"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_ID,
+    torch_dtype=torch.bfloat16,
+    attn_implementation="sdpa",
+).to("cuda")
+model.eval()
+
+DEFAULT_SYSTEM = "You are a helpful, concise assistant."
+
+
+@spaces.GPU(duration=90)
+def chat(
+    message: str,
+    history: list,
+    system_prompt: str = DEFAULT_SYSTEM,
+    max_new_tokens: int = 512,
+    temperature: float = 0.7,
+    top_p: float = 0.9,
+):
+    """Chat with the fable-traces (Qwen3-4B-Instruct finetune) model.
+
+    Args:
+        message: the user's latest message.
+        history: prior conversation turns (managed by Gradio ChatInterface).
+        system_prompt: instruction that steers the assistant's behaviour.
+        max_new_tokens: maximum number of tokens to generate in the reply.
+        temperature: sampling temperature; higher is more random.
+        top_p: nucleus sampling probability mass.
+    """
+    messages = []
+    if system_prompt and system_prompt.strip():
+        messages.append({"role": "system", "content": system_prompt.strip()})
+    for turn in history:
+        if isinstance(turn, dict):
+            messages.append({"role": turn["role"], "content": turn["content"]})
+        else:
+            user_msg, assistant_msg = turn
+            if user_msg:
+                messages.append({"role": "user", "content": user_msg})
+            if assistant_msg:
+                messages.append({"role": "assistant", "content": assistant_msg})
+    messages.append({"role": "user", "content": message})
+
+    inputs = tokenizer.apply_chat_template(
+        messages,
+        add_generation_prompt=True,
+        return_tensors="pt",
+    ).to(model.device)
+
+    streamer = TextIteratorStreamer(
+        tokenizer, skip_prompt=True, skip_special_tokens=True
+    )
+
+    do_sample = temperature > 0
+    gen_kwargs = dict(
+        input_ids=inputs,
+        streamer=streamer,
+        max_new_tokens=int(max_new_tokens),
+        do_sample=do_sample,
+        pad_token_id=tokenizer.pad_token_id or tokenizer.eos_token_id,
+    )
+    if do_sample:
+        gen_kwargs["temperature"] = float(temperature)
+        gen_kwargs["top_p"] = float(top_p)
+
+    thread = Thread(target=model.generate, kwargs=gen_kwargs)
+    thread.start()
+
+    partial = ""
+    for token in streamer:
+        partial += token
+        yield partial
+
+
+CSS = """
+#col-container { max-width: 900px; margin: 0 auto; }
+.dark .gradio-container { color: var(--body-text-color); }
+"""
+
+with gr.Blocks(theme=gr.themes.Citrus(), css=CSS) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown(
+            """
+            # 📖 fable-traces
+            Chat with [`AliesTaha/fable-traces`](https://huggingface.co/AliesTaha/fable-traces),
+            a compact instruction-tuned model built on **Qwen3-4B-Instruct-2507**.
+            Tuned for short, conversational replies.
+            """
+        )
+
+        with gr.Accordion("Advanced settings", open=False):
+            system_prompt = gr.Textbox(
+                label="System prompt",
+                value=DEFAULT_SYSTEM,
+                lines=2,
+            )
+            max_new_tokens = gr.Slider(
+                minimum=16, maximum=2048, value=512, step=16,
+                label="Max new tokens",
+            )
+            temperature = gr.Slider(
+                minimum=0.0, maximum=1.5, value=0.7, step=0.05,
+                label="Temperature (0 = greedy)",
+            )
+            top_p = gr.Slider(
+                minimum=0.1, maximum=1.0, value=0.9, step=0.05,
+                label="Top-p",
+            )
+
+        gr.ChatInterface(
+            fn=chat,
+            type="messages",
+            additional_inputs=[system_prompt, max_new_tokens, temperature, top_p],
+            examples=[
+                ["Tell me something interesting."],
+                ["Write a two-line poem about the desert at night."],
+                ["Explain what a large language model is in one sentence."],
+                ["Give me three tips for staying focused while studying."],
+            ],
+            cache_examples=False,
+        )
+
+if __name__ == "__main__":
+    demo.launch(mcp_server=True)

requirements.txt

@@ -0,0 +1,2 @@
+transformers
+accelerate