Update modeling_fastesm.py

modeling_fastesm.py

@@ -4,7 +4,7 @@ from torch.nn import functional as F
 from torch.utils.data import Dataset, DataLoader
 from typing import Optional, Tuple, Union
 from einops import rearrange
-from transformers import PreTrainedModel, PretrainedConfig, EsmTokenizer
+from transformers import PreTrainedModel, PretrainedConfig
 from transformers.modeling_outputs import (
     MaskedLMOutput,
     BaseModelOutputWithPastAndCrossAttentions,
@@ -145,13 +145,6 @@ class EsmEmbeddings(nn.Module):
     def forward(
         self, input_ids=None, attention_mask=None, position_ids=None, inputs_embeds=None, past_key_values_length=0
     ):
-        if position_ids is None:
-            if input_ids is not None:
-                # Create the position ids from the input token ids. Any padded tokens remain padded.
-                position_ids = create_position_ids_from_input_ids(input_ids, self.padding_idx, past_key_values_length)
-            else:
-                position_ids = self.create_position_ids_from_inputs_embeds(inputs_embeds)
-
         if inputs_embeds is None:
             inputs_embeds = self.word_embeddings(input_ids)
 
@@ -346,7 +339,6 @@ class FastEsmPreTrainedModel(PreTrainedModel):
     config_class = FastEsmConfig
     base_model_prefix = "fastesm"
     supports_gradient_checkpointing = True
-    tokenizer = EsmTokenizer.from_pretrained("facebook/esm2_t33_650M_UR50D")
     def _init_weights(self, module):
         """Initialize the weights"""
         if isinstance(module, nn.Linear):