When I wanted to specify the evo-1-8k-base model for tokenizer, Evo kept using evo-1-131k-base instead

Hello, Thank you for developing such an excellent foundation model. When I tried to use Evo's evo-1-8k-base model for tokenizer, Evo kept reporting errors about evo-1-131k-base (see below). Do you have any suggestions? Any help will be appreciated.

Feng

>> from transformers import AutoTokenizer
>> 
>> model_name = 'togethercomputer/evo-1-8k-base'
>> tokenizer = AutoTokenizer.from_pretrained(model_name, 
>>    trust_remote_code=True, revision="1.1_fix")

/xxx/miniconda3/envs/evo-design/lib/python3.11/site-packages/huggingface_hub/file_download.py:797: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
  warnings.warn(
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[20], line 4
      3 model_name = 'togethercomputer/evo-1-8k-base'
----> 4 tokenizer = AutoTokenizer.from_pretrained(model_name,
      5         trust_remote_code=True, revision="1.1_fix")

File /xxx/miniconda3/envs/evo-design/lib/python3.11/site-packages/transformers/models/auto/tokenization_auto.py:721, in AutoTokenizer.from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs)    715         else:
    716             raise ValueError(
    717                 "This tokenizer cannot be instantiated. Please make sure you have `sentencepiece` installed "
    718                 "in order to use this tokenizer."
    719             )
--> 721 raise ValueError(
    722     f"Unrecognized configuration class {config.__class__} to build an AutoTokenizer.\n"
    723     f"Model type should be one of {', '.join(c.__name__ for c in TOKENIZER_MAPPING.keys())}."
    724 )

ValueError: Unrecognized configuration class <class 'transformers_modules.togethercomputer.evo-1-131k-base.567369e9825aa08b3de4b122fca34fac6a890602.configuration_hyena.StripedHyenaConfig'> to build an AutoTokenizer.
Model type should be one of AlbertConfig, AlignConfig, BartConfig, BertConfig, BertGenerationConfig, BigBirdConfig, BigBirdPegasusConfig, BioGptConfig, BlenderbotConfig, BlenderbotSmallConfig, BlipConfig, Blip2Config, BloomConfig, BridgeTowerConfig, CamembertConfig, CanineConfig, ChineseCLIPConfig, ClapConfig, CLIPConfig, CLIPSegConfig, CodeGenConfig, ConvBertConfig, CpmAntConfig, CTRLConfig, Data2VecTextConfig, DebertaConfig, DebertaV2Config, DistilBertConfig, DPRConfig, ElectraConfig, ErnieConfig, ErnieMConfig, EsmConfig, FlaubertConfig, FNetConfig, FSMTConfig, FunnelConfig, GitConfig, GPT2Config, GPT2Config, GPTBigCodeConfig, GPTNeoConfig, GPTNeoXConfig, GPTNeoXJapaneseConfig, GPTJConfig, GPTSanJapaneseConfig, GroupViTConfig, HubertConfig, IBertConfig, JukeboxConfig, LayoutLMConfig, LayoutLMv2Config, LayoutLMv3Config, LEDConfig, LiltConfig, LlamaConfig, LongformerConfig, LongT5Config, LukeConfig, LxmertConfig, M2M100Config, MarianConfig, MBartConfig, MegaConfig, MegatronBertConfig, MgpstrConfig, MobileBertConfig, MPNetConfig, MT5Config, MvpConfig, NezhaConfig, NllbMoeConfig, NystromformerConfig, OneFormerConfig, OpenAIGPTConfig, OPTConfig, OwlViTConfig, PegasusConfig, PegasusXConfig, PerceiverConfig, Pix2StructConfig, PLBartConfig, ProphetNetConfig, QDQBertConfig, RagConfig, RealmConfig, ReformerConfig, RemBertConfig, RetriBertConfig, RobertaConfig, RobertaPreLayerNormConfig, RoCBertConfig, RoFormerConfig, RwkvConfig, Speech2TextConfig, Speech2Text2Config, SpeechT5Config, SplinterConfig, SqueezeBertConfig, SwitchTransformersConfig, T5Config, TapasConfig, TransfoXLConfig, ViltConfig, VisualBertConfig, Wav2Vec2Config, Wav2Vec2ConformerConfig, WhisperConfig, XCLIPConfig, XGLMConfig, XLMConfig, XLMProphetNetConfig, XLMRobertaConfig, XLMRobertaXLConfig, XLNetConfig, XmodConfig, YosoConfig.

evo-design / evo

When I wanted to specify the evo-1-8k-base model for tokenizer, Evo kept using evo-1-131k-base instead #89