'<' not supported between instances of 'str' and 'int'

Hello, when `nlp = assemble("config.cfg")`, I get the following Traceback, I use the dolly config.cfg example from here : https://spacy.io/usage/large-language-models#usage. Thanks in advance !

```
File [/usr/local/lib/python3.9/dist-packages/spacy_llm/util.py:48](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/spacy_llm/util.py:48), in assemble(config_path, overrides)
46 config_path = Path(config_path)
47 config = load_config(config_path, overrides=overrides, interpolate=False)
---> 48 return assemble_from_config(config)

File [/usr/local/lib/python3.9/dist-packages/spacy_llm/util.py:28](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/spacy_llm/util.py:28), in assemble_from_config(config)
22 def assemble_from_config(config: Config) -> Language:
23 """Assemble a spaCy pipeline from a confection Config object.
24
25 config (Config): Config to load spaCy pipeline from.
26 RETURNS (Language): An initialized spaCy pipeline.
27 """
---> 28 nlp = load_model_from_config(config, auto_fill=True)
29 config = config.interpolate()
30 sourced = get_sourced_components(config)

File [/usr/local/lib/python3.9/dist-packages/spacy/util.py:587](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/spacy/util.py:587), in load_model_from_config(config, meta, vocab, disable, enable, exclude, auto_fill, validate)
584 # This will automatically handle all codes registered via the languages
585 # registry, including custom subclasses provided via entry points
586 lang_cls = get_lang_class(nlp_config["lang"])
--> 587 nlp = lang_cls.from_config(
588 config,
589 vocab=vocab,
590 disable=disable,
591 enable=enable,
592 exclude=exclude,
593 auto_fill=auto_fill,
594 validate=validate,
595 meta=meta,
596 )
597 return nlp

File [/usr/local/lib/python3.9/dist-packages/spacy/language.py:1864](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/spacy/language.py:1864), in Language.from_config(cls, config, vocab, disable, enable, exclude, meta, auto_fill, validate)
1861 factory = pipe_cfg.pop("factory")
1862 # The pipe name (key in the config) here is the unique name
1863 # of the component, not necessarily the factory
-> 1864 nlp.add_pipe(
1865 factory,
1866 name=pipe_name,
1867 config=pipe_cfg,
1868 validate=validate,
1869 raw_config=raw_config,
1870 )
1871 else:
1872 assert "source" in pipe_cfg

File [/usr/local/lib/python3.9/dist-packages/spacy/language.py:821](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/spacy/language.py:821), in Language.add_pipe(self, factory_name, name, before, after, first, last, source, config, raw_config, validate)
817 pipe_component, factory_name = self.create_pipe_from_source(
818 factory_name, source, name=name
819 )
820 else:
--> 821 pipe_component = self.create_pipe(
822 factory_name,
823 name=name,
824 config=config,
825 raw_config=raw_config,
826 validate=validate,
827 )
828 pipe_index = self._get_pipe_index(before, after, first, last)
829 self._pipe_meta[name] = self.get_factory_meta(factory_name)

File [/usr/local/lib/python3.9/dist-packages/spacy/language.py:709](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/spacy/language.py:709), in Language.create_pipe(self, factory_name, name, config, raw_config, validate)
706 cfg = {factory_name: config}
707 # We're calling the internal _fill here to avoid constructing the
708 # registered functions twice
--> 709 resolved = registry.resolve(cfg, validate=validate)
710 filled = registry.fill({"cfg": cfg[factory_name]}, validate=validate)["cfg"]
711 filled = Config(filled)

File [/usr/local/lib/python3.9/dist-packages/confection/__init__.py:759](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/confection/__init__.py:759), in registry.resolve(cls, config, schema, overrides, validate)
750 @classmethod
751 def resolve(
752 cls,
(...)
757 validate: bool = True,
758 ) -> Dict[str, Any]:
--> 759 resolved, _ = cls._make(
760 config, schema=schema, overrides=overrides, validate=validate, resolve=True
761 )
762 return resolved

File [/usr/local/lib/python3.9/dist-packages/confection/__init__.py:808](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/confection/__init__.py:808), in registry._make(cls, config, schema, overrides, resolve, validate)
806 if not is_interpolated:
807 config = Config(orig_config).interpolate()
--> 808 filled, _, resolved = cls._fill(
809 config, schema, validate=validate, overrides=overrides, resolve=resolve
810 )
811 filled = Config(filled, section_order=section_order)
812 # Check that overrides didn't include invalid properties not in config

File [/usr/local/lib/python3.9/dist-packages/confection/__init__.py:863](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/confection/__init__.py:863), in registry._fill(cls, config, schema, validate, resolve, parent, overrides)
861 schema.__fields__[key] = copy_model_field(field, Any)
862 promise_schema = cls.make_promise_schema(value, resolve=resolve)
--> 863 filled[key], validation[v_key], final[key] = cls._fill(
864 value,
865 promise_schema,
866 validate=validate,
867 resolve=resolve,
868 parent=key_parent,
869 overrides=overrides,
870 )
871 reg_name, func_name = cls.get_constructor(final[key])
872 args, kwargs = cls.parse_args(final[key])

File [/usr/local/lib/python3.9/dist-packages/confection/__init__.py:880](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/confection/__init__.py:880), in registry._fill(cls, config, schema, validate, resolve, parent, overrides)
877 getter = cls.get(reg_name, func_name)
878 # We don't want to try/except this and raise our own error
879 # here, because we want the traceback if the function fails.
--> 880 getter_result = getter(*args, **kwargs)
881 else:
882 # We're not resolving and calling the function, so replace
883 # the getter_result with a Promise class
884 getter_result = Promise(
885 registry=reg_name, name=func_name, args=args, kwargs=kwargs
886 )

File [/usr/local/lib/python3.9/dist-packages/spacy_llm/models/hf/dolly.py:63](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/spacy_llm/models/hf/dolly.py:63), in dolly_hf(name, config_init, config_run)
50 @registry.llm_models("spacy.Dolly.v1")
51 def dolly_hf(
52 name: Dolly.MODEL_NAMES,
53 config_init: Optional[Dict[str, Any]] = SimpleFrozenDict(),
54 config_run: Optional[Dict[str, Any]] = SimpleFrozenDict(),
55 ) -> Callable[[Iterable[str]], Iterable[str]]:
56 """Generates Dolly instance that can execute a set of prompts and return the raw responses.
57 name (Literal): Name of the Dolly model. Has to be one of Dolly.get_model_names().
58 config_init (Optional[Dict[str, Any]]): HF config for initializing the model.
(...)
61 the raw responses.
62 """
---> 63 return Dolly(name=name, config_init=config_init, config_run=config_run)

File [/usr/local/lib/python3.9/dist-packages/spacy_llm/models/hf/base.py:39](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/spacy_llm/models/hf/base.py:39), in HuggingFace.__init__(self, name, config_init, config_run)
37 HuggingFace.check_installation()
38 self._check_model()
---> 39 self._model = self.init_model()

File [/usr/local/lib/python3.9/dist-packages/spacy_llm/models/hf/dolly.py:17](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/spacy_llm/models/hf/dolly.py:17), in Dolly.init_model(self)
13 def init_model(self) -> Any:
14 """Sets up HF model and needed utilities.
15 RETURNS (Any): HF model.
16 """
---> 17 return transformers.pipeline(
18 model=self._name, return_full_text=False, **self._config_init
19 )

File [/usr/local/lib/python3.9/dist-packages/transformers/pipelines/__init__.py:767](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/transformers/pipelines/__init__.py:767), in pipeline(task, model, config, tokenizer, feature_extractor, framework, revision, use_fast, use_auth_token, device_map, torch_dtype, trust_remote_code, model_kwargs, pipeline_class, **kwargs)
764 if feature_extractor is not None:
765 kwargs["feature_extractor"] = feature_extractor
--> 767 return pipeline_class(model=model, framework=framework, task=task, **kwargs)

File [~/.cache/huggingface/modules/transformers_modules/databricks/dolly-v2-3b/f6c9be08f16fe4d3a719bee0a4a7c7415b5c65df/instruct_pipeline.py:74](https://file+.vscode-resource.vscode-cdn.net/Users/user/Documents/lili/nlp-bricks/synthetic_data_annotation/~/.cache/huggingface/modules/transformers_modules/databricks/dolly-v2-3b/f6c9be08f16fe4d3a719bee0a4a7c7415b5c65df/instruct_pipeline.py:74), in InstructionTextGenerationPipeline.__init__(self, do_sample, max_new_tokens, top_p, top_k, *args, **kwargs)
61 def __init__(
62 self, *args, do_sample: bool = True, max_new_tokens: int = 256, top_p: float = 0.92, top_k: int = 0, **kwargs
63 ):
64 """Initialize the pipeline
65
66 Args:
(...)
72 Defaults to 0.
73 """
---> 74 super().__init__(*args, do_sample=do_sample, max_new_tokens=max_new_tokens, top_p=top_p, top_k=top_k,
75 **kwargs)

File [/usr/local/lib/python3.9/dist-packages/transformers/pipelines/base.py:768](https://file+.vscode-resource.vscode-cdn.net/usr/local/lib/python3.9/dist-packages/transformers/pipelines/base.py:768), in Pipeline.__init__(self, model, tokenizer, feature_extractor, modelcard, framework, task, args_parser, device, binary_output, **kwargs)
766 self.device = device
767 else:
--> 768 self.device = device if framework == "tf" else torch.device("cpu" if device < 0 else f"cuda:{device}")
769 self.binary_output = binary_output
771 # Special handling

TypeError: '<' not supported between instances of 'str' and 'int'