# HF agents course error in duplicating my first agent

> Source: <https://discuss.huggingface.co/t/hf-agents-course-error-in-duplicating-my-first-agent/178636#post_2>
> Published: 2026-08-14 12:29:36+00:00

i tried to duplicate the agents example using zeroGPU cz it’s the free one , but i get this error runtime error

Hmm… at first I thought, “Why ZeroGPU??” …but apparently with a Free account now, ZeroGPU is basically the only compute-backed Gradio option you can host yourself… I didn’t know that.

The immediate error:

```
No @spaces.GPU function detected during startup
```

does not look like a `smolagents`

or Qwen error. It is ZeroGPU rejecting the Space at startup because it cannot find a function decorated with `@spaces.GPU`

.

For **this particular course template**, I would take the minimal route first rather than trying to move the agent itself onto the GPU.

Add this near the imports in `app.py`

:

``` python
import spaces

@spaces.GPU(duration=1)
def dummy_gpu():
    return None
```

and leave the function unused.

The documented/intended ZeroGPU pattern is, of course, to decorate an actual GPU-dependent function; see the [ZeroGPU documentation](https://huggingface.co/docs/hub/spaces-zerogpu). The decorator causes a GPU to be allocated when the decorated function is called and released afterward.

But this course agent does **not actually need a Space GPU for its LLM inference**, so I tested the unused dummy-decorator variant in a duplicated ZeroGPU Space, and it was enough to get past this startup check.

I would also make one tiny preventive edit to `prompts.yaml`

while you are there:

```
"final_answer":
  "pre_messages": ""
  "post_messages": ""
```

Add that as a top-level section near the end of the file.

And make sure that your duplicated Space has an `HF_TOKEN`

**Secret** with inference permission. Secrets are deliberately not copied into duplicated Spaces; the [course itself asks you to recreate HF_TOKEN](https://huggingface.co/learn/agents-course/unit1/tutorial), and the

For the smallest-change course path, I would therefore do only this initially:

```
1. Keep the template's smolagents==1.13.0 for now.
2. Add the unused @spaces.GPU dummy.
3. Add the three-line final_answer section to prompts.yaml.
4. Recreate/check HF_TOKEN.
5. Rebuild.
```

I would **not** upgrade all of `smolagents`

at the same time unless you actually want to modernize the template, because there is a separate version-drift problem hiding behind this one.

The important conceptual warning is that **getting the ZeroGPU Space to start does not mean that Qwen-32B is now running for free on ZeroGPU**. Those are two different systems.

```
ZeroGPU
    → hosts the Gradio Space / allocates GPU to @spaces.GPU calls

InferenceClientModel
    → calls a remotely hosted model through Hugging Face Inference Providers
```

The [current course page](https://huggingface.co/learn/agents-course/unit1/tutorial) explicitly uses:

```
model = InferenceClientModel(
    max_tokens=2096,
    temperature=0.5,
    model_id="Qwen/Qwen2.5-Coder-32B-Instruct",
    custom_role_conversions=None,
)
```

and describes Qwen2.5-Coder-32B-Instruct as being accessed through the serverless API.

So there are really several independent traps layered on top of each other here.

Why choosing ZeroGPU on a Free account actually makes sense nowSo my mental model for this particular failure would be:

```
Trap 1:
Free-account Space policy
    ↓
ZeroGPU becomes the practical free Gradio-hosting route

Trap 2:
ZeroGPU expects @spaces.GPU
    ↓
old course template has none
    ↓
"No @spaces.GPU function detected"

Trap 3:
getting ZeroGPU to start does NOT put Qwen-32B on ZeroGPU
    ↓
the LLM still uses Inference Providers
    ↓
separate inference credits / provider limits apply

Trap 4:
the current lesson and duplicate template have version drift
    ↓
HfApiModel vs InferenceClientModel
smolagents 1.13.0 pin
missing final_answer prompt
other migration differences
```

For **your immediate problem**, though, I would not try to solve all four layers at once.

I would start with just:

``` python
import spaces

@spaces.GPU(duration=1)
def dummy_gpu():
    return None
```

plus:

```
"final_answer":
  "pre_messages": ""
  "post_messages": ""
```

make sure `HF_TOKEN`

exists, and rebuild.

If that starts, then the original ZeroGPU error is solved. Any error after that is much easier to classify as an inference/token/provider issue or as the separate template-version issue above, rather than one giant mysterious Space failure.