Repository: huggingface/lighteval
Issue: [BUG] BuilderConfig doesn't have a 'trust_remote_code' key error
Root cause: Environment Incompatibility

## Describe the bug

Running lighteval "[Using the Python API](https://github.com/huggingface/lighteval/wiki/Using-the-Python-API)" example but using Transformer model, e.g. HuggingFaceTB/SmolLM2-360M-Instruct or Qwen/Qwen2.5-0.5B-Instruct throws error:

```
ValueError: BuilderConfig BuilderConfig(name='econometrics', version=1.0.0, data_dir=None, data_files=None, description='MMLU Subject econometrics') doesn't have a 'trust_remote_code' key.
```

The only difference of my code compared to sample from docs is (i) the task definition and (ii) I am instantiating a ModelConfig from BaseModelConfig instead of VLLMModelConfig since I would like to use HuggingFace Transformers instead of VLLM.

## Stack trace
https://pastebin.com/bvF3sxnE

## To Reproduce

```python
import lighteval
from lighteval.logging.evaluation_tracker import EvaluationTracker
from lighteval.models.model_config import BaseModelConfig
from lighteval.pipeline import ParallelismManager, Pipeline, PipelineParameters
from lighteval.utils.utils import EnvConfig
from lighteval.utils.imports import is_accelerate_available
from datetime import timedelta
from accelerate import Accelerator, InitProcessGroupKwargs


if is_accelerate_available():
    from accelerate import Accelerator, InitProcessGroupKwargs
    accelerator = Accelerator(kwargs_handlers=[InitProcessGroupKwargs(timeout=timedelta(seconds=3000))])
else:
    accelerator = None

evaluation_tracker = EvaluationTracker(
    output_dir="./results",
    save_details=True,
    push_to_hub=False,
    hub_results_org="your user name"   
)


pipeline_params = PipelineParameters(
    launcher_type=ParallelismManager.ACCELERATE,
    env_config=EnvConfig(cache_dir="tmp/"),
    # Remove the 2 parameters below once your configuration is tested
    override_batch_size=1,
    max_samples=10
)


model_config = BaseModelConfig(
        pretrained="HuggingFaceTB/SmolLM2-360M-Instruct",
        dtype="float16",
        use_chat_template=True,
        trust_remote_code = True
)

task = "leaderboard|mmlu:econometrics|0|0"

pipeline = Pipeline(
    tasks=task,
    pipeline_parameters=pipeline_params,
    evaluation_tracker=evaluation_tracker,
    model_config=model_config
)
```

## Expected behavior

Task is performed successfully and results are generated locally.

## Version info

python = "^3.11"
lighteval = {extras = ["accelerate"], version = "^0.6.2"}


Hi! Can you share your datasets version?

Hi @clefourrier , many thanks for the quick response.
I had not installed datasets. The issue now has been solved after installing it!
Thank you so much again for the response and for creating such a great product for evals!

Minor suggestions: 
- Add `datasets` to the "Installation" [wiki page](https://github.com/huggingface/lighteval/wiki/Installation).
- Add informative error messages that would indicate `datasets` dependency is missing for the aforementioned scenario.

Hi @souzatharsis !
Thanks for using our lib! :)
Datasets should be installed automatically if you follow the installation steps - can you tell me how you installed the library?

```
poetry add lighteval[accelerate]
```

Hm interesting - cc @NathanHB for viz