Download configuration_lucavirus.py from LucaGroup/LucaVirus-mask-step3.8M: direct link, hf CLI and curl.
- Browser
- Download file 4 kB
-
https://huggingface.co/LucaGroup/LucaVirus-mask-step3.8M/resolve/main/configuration_lucavirus.py
- Command line
-
hf download hf://LucaGroup/LucaVirus-mask-step3.8M/configuration_lucavirus.py
-
curl -L -o configuration_lucavirus.py https://huggingface.co/LucaGroup/LucaVirus-mask-step3.8M/resolve/main/configuration_lucavirus.py
4 kB
| #!/usr/bin/env python | |
| # encoding: utf-8 | |
| ''' | |
| @license: (C) Copyright 2025, Hey. | |
| @author: Hey | |
| @email: sanyuan.hy@alibaba-inc.com | |
| @tel: 137****6540 | |
| @datetime: 2025/12/30 11:34 | |
| @project: lucavirus | |
| @file: tokenization_lucavirus | |
| @desc: tokenization_lucavirus | |
| ''' | |
| from typing import Literal | |
| from transformers import PretrainedConfig | |
| class LucaVirusConfig(PretrainedConfig): | |
| model_type = "lucavirus" | |
| def __init__( | |
| self, | |
| vocab_size: int = 39, | |
| pad_token_id: int = 0, | |
| unk_token_id: int = 1, | |
| bos_token_id: int = 2, | |
| eos_token_id: int = 3, | |
| sep_token_id: int = 3, | |
| mask_token_id: int = 4, | |
| hidden_act: str = "gelu", | |
| max_position_embeddings: int = 4096, | |
| type_vocab_size: int = 2, | |
| num_hidden_layers: int = 20, | |
| num_attention_heads: int = 40, | |
| hidden_size: int = 2560, | |
| ffn_dim: int = 10240, | |
| no_position_embeddings: bool = True, | |
| no_token_type_embeddings: bool = False, | |
| alphabet: str = "gene_prot", | |
| token_dropout: bool = False, | |
| attention_probs_dropout_prob: float = 0.0, | |
| hidden_dropout_prob: float = 0.0, | |
| use_embed_layer_norm: bool = False, | |
| use_last_layer_norm: bool = True, | |
| embed_scale: float = 1.0, | |
| ignore_index: int = -100, | |
| layer_norm_eps: float = 1e-12, | |
| initializer_range: float = 0.02, | |
| task_level: Literal["seq_level", "token_level"] = "seq_level", | |
| task_type: Literal["embedding", "mlm", "multi_class", "binary_class", "regression", "multi_label"] = "embedding", | |
| classifier_num_labels: int = -1, | |
| classifier_dropout_prob: float = 0.1, | |
| classifier_pooling_type: Literal["cls", "value_attention", "context_attention", "mean"] = "value_attention", | |
| classifier_loss_type: Literal["binary_cross_entropy", "cross_entropy", "mse", "mae"] = "cross_entropy", | |
| classifier_loss_reduction: Literal["mean", "sum", "none"] = "mean", | |
| classifier_pos_weight: float=1.0, | |
| classifier_weight: list=None, | |
| tie_word_embeddings: bool=True, | |
| **kwargs | |
| ): | |
| super().__init__( | |
| tie_word_embeddings=tie_word_embeddings, | |
| pad_token_id=pad_token_id, | |
| **kwargs | |
| ) | |
| self.alphabet = alphabet | |
| self.vocab_size = vocab_size | |
| self.max_position_embeddings = max_position_embeddings | |
| self.type_vocab_size = type_vocab_size | |
| self.no_token_type_embeddings = no_token_type_embeddings | |
| self.no_position_embeddings = no_position_embeddings | |
| self.num_hidden_layers = num_hidden_layers | |
| self.hidden_size = hidden_size | |
| self.num_attention_heads = num_attention_heads | |
| self.ffn_dim = ffn_dim | |
| self.token_dropout = token_dropout | |
| self.attention_probs_dropout_prob = attention_probs_dropout_prob | |
| self.hidden_dropout_prob = hidden_dropout_prob | |
| self.classifier_dropout_prob = classifier_dropout_prob | |
| self.ignore_index = ignore_index | |
| self.use_embed_layer_norm = use_embed_layer_norm | |
| self.use_last_layer_norm = use_last_layer_norm | |
| self.embed_scale = embed_scale | |
| self.layer_norm_eps = layer_norm_eps | |
| self.initializer_range = initializer_range | |
| self.unk_token_id = unk_token_id | |
| self.bos_token_id = bos_token_id | |
| self.eos_token_id = eos_token_id | |
| self.sep_token_id = sep_token_id | |
| self.mask_token_id = mask_token_id | |
| self.hidden_act = hidden_act | |
| self.classifier_num_labels = classifier_num_labels | |
| self.classifier_pooling_type = classifier_pooling_type | |
| self.task_level = task_level | |
| self.task_type = task_type | |
| self.classifier_loss_type = classifier_loss_type | |
| self.classifier_loss_reduction = classifier_loss_reduction | |
| self.classifier_pos_weight = classifier_pos_weight | |
| self.classifier_weight = classifier_weight | |
| __all__ = ["LucaVirusConfig"] |