Update README.md

README.md

@@ -33,7 +33,7 @@ model-index:
     dataset:
       name: Multilingual LibriSpeech
       type: facebook/multilingual_librispeech
-      config: german
+      config: de
       split: test
       args:
         language: de
@@ -140,8 +140,6 @@ The NeMo toolkit [3] was used for training the models for over several hundred e
 
 The tokenizers for these models were built using the text transcripts of the train set with this [script](https://github.com/NVIDIA/NeMo/blob/main/scripts/tokenizers/process_asr_text_tokenizer.py).
 
-The checkpoint of the language model used as the neural rescorer can be found [here](https://ngc.nvidia.com/catalog/models/nvidia:nemo:asrlm_en_transformer_large_ls). You may find more info on how to train and use language models for ASR models here: [ASR Language Modeling](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/asr/asr_language_modeling.html)
-
 ### Datasets
 
 All the models in this collection are trained on a composite dataset (NeMo ASRSET) comprising of several thousand hours of English speech: