"KeyError" when running example code

[chricke]

I tried to run the demo code from https://huggingface.co/KRLabsOrg/lettucedect-610m-eurobert-de-v1 but get a KeyError when loading the model.

`from lettucedetect.models.inference import HallucinationDetector

detector = HallucinationDetector(
method="transformer",
model_path="KRLabsOrg/lettucedect-610m-eurobert-de-v1",
lang="de",
trust_remote_code=True
)`

After downloading the model and files it returns this every time I try to use the model:

`---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[5], line 1
----> 1 detector = HallucinationDetector(
2 method="transformer",
3 model_path="KRLabsOrg/lettucedect-610m-eurobert-de-v1",
4 lang="de",
5 trust_remote_code=True
6 )

File ~/miniconda3/envs/hallucination_detection_312/lib/python3.12/site-packages/lettucedetect/models/inference.py:20, in HallucinationDetector.init(self, method, **kwargs)
19 def init(self, method: str = "transformer", **kwargs):
---> 20 self.detector = make_detector(method, **kwargs)

File ~/miniconda3/envs/hallucination_detection_312/lib/python3.12/site-packages/lettucedetect/detectors/factory.py:21, in make_detector(method, **kwargs)
18 if method == "transformer":
19 from lettucedetect.detectors.transformer import TransformerDetector
---> 21 return TransformerDetector(**kwargs)
22 elif method == "llm":
23 from lettucedetect.detectors.llm import LLMDetector

File ~/miniconda3/envs/hallucination_detection_312/lib/python3.12/site-packages/lettucedetect/detectors/transformer.py:33, in TransformerDetector.init(self, model_path, max_length, device, lang, **tok_kwargs)
31 self.lang, self.max_length = lang, max_length
32 self.tokenizer = AutoTokenizer.from_pretrained(model_path, **tok_kwargs)
---> 33 self.model = AutoModelForTokenClassification.from_pretrained(model_path, **tok_kwargs)
34 self.device = device or (
35 torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
36 )
37 self.model.to(self.device).eval()

File ~/miniconda3/envs/hallucination_detection_312/lib/python3.12/site-packages/transformers/models/auto/auto_factory.py:367, in _BaseAutoModelClass.from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
365 model_class.register_for_auto_class(auto_class=cls)
366 model_class = add_generation_mixin_to_remote_model(model_class)
--> 367 return model_class.from_pretrained(
368 pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs
369 )
370 elif type(config) in cls._model_mapping:
371 model_class = _get_model_class(config, cls._model_mapping)

File ~/miniconda3/envs/hallucination_detection_312/lib/python3.12/site-packages/transformers/modeling_utils.py:4021, in PreTrainedModel.from_pretrained(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, weights_only, *model_args, **kwargs)
4018 config = copy.deepcopy(config) # We do not want to modify the config inplace in from_pretrained.
4019 with ContextManagers(model_init_context):
4020 # Let's make sure we don't run the init function of buffer modules
-> 4021 model = cls(config, *model_args, **model_kwargs)
4023 if hf_quantizer is not None: # replace module with quantized modules (does not touch weights)
4024 hf_quantizer.preprocess_model(
4025 model=model,
4026 dtype=dtype,
(...) 4029 use_kernels=use_kernels,
4030 )

File ~/.cache/huggingface/modules/transformers_modules/EuroBERT/EuroBERT_hyphen_610m/d9af784ed20db6c2096e335ec6a67dd4a219924c/modeling_eurobert.py:892, in EuroBertForTokenClassification.init(self, config)
890 super().init(config)
891 self.num_labels = config.num_labels
--> 892 self.model = EuroBertModel(config)
894 self.classifier = nn.Linear(config.hidden_size, config.num_labels)
895 self.post_init()

File ~/.cache/huggingface/modules/transformers_modules/EuroBERT/EuroBERT_hyphen_610m/d9af784ed20db6c2096e335ec6a67dd4a219924c/modeling_eurobert.py:484, in EuroBertModel.init(self, config)
480 self.layers = nn.ModuleList(
481 [EuroBertDecoderLayer(config, layer_idx) for layer_idx in range(config.num_hidden_layers)]
482 )
483 self.norm = EuroBertRMSNorm(config.hidden_size, eps=config.rms_norm_eps)
--> 484 self.rotary_emb = EuroBertRotaryEmbedding(config=config)
485 self.gradient_checkpointing = False
486 self.mask_converter = AttentionMaskConverter(is_causal=False)

File ~/.cache/huggingface/modules/transformers_modules/EuroBERT/EuroBERT_hyphen_610m/d9af784ed20db6c2096e335ec6a67dd4a219924c/modeling_eurobert.py:268, in EuroBertRotaryEmbedding.init(self, config, device)
265 self.original_max_seq_len = config.max_position_embeddings
267 self.config = config
--> 268 self.rope_init_fn = ROPE_INIT_FUNCTIONS[self.rope_type]
270 inv_freq, self.attention_scaling = self.rope_init_fn(self.config, device)
271 self.register_buffer("inv_freq", inv_freq, persistent=False)

KeyError: 'default'`