dd

LID-40-3-2000000-1-4.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:987a2e16b216eb22f0342beb75874e9748cf6bceeb4ac75f6e2efc3414e74961
+size 32001553

config.json

@@ -1,8 +1,9 @@
 {
-  "_name_or_path": "experiments_final/model_dbmdz_bert_medium_historic_multilingual_cased_max_sequence_length_512_epochs_5_run_extended_suffix_baseline/checkpoint-450",
+  "_name_or_path": "emanuelaboros/ner-stacked-bert-multilingual",
   "architectures": [
     "ExtendedMultitaskModelForTokenClassification"
   ],
+  "filename": "LID-40-3-2000000-1-4.bin",
   "attention_probs_dropout_prob": 0.1,
   "auto_map": {
     "AutoConfig": "configuration_stacked.ImpressoConfig",

modeling_stacked.py

@@ -5,7 +5,7 @@ from transformers import PreTrainedModel, AutoModel, AutoConfig, BertConfig
 from torch.nn import CrossEntropyLoss
 from typing import Optional, Tuple, Union
 import logging, json, os
-
+import floret
 from .configuration_stacked import ImpressoConfig
 
 logger = logging.getLogger(__name__)
@@ -29,6 +29,8 @@ class ExtendedMultitaskModelForTokenClassification(PreTrainedModel):
         self.bert = AutoModel.from_pretrained(
             config.pretrained_config["_name_or_path"], config=config.pretrained_config
         )
+        self.model_floret = floret.load_model(self.config.filename)
+        print(f"Model loaded: {self.model_floret}")
         if "classifier_dropout" not in config.__dict__:
             classifier_dropout = 0.1
         else: