Update README.md

README.md

@@ -9,7 +9,7 @@ tags:
 - xlsr-fine-tuning-week
 license: apache-2.0
 model-index:
-- name: XLSR Wav2Vec2 Swedish by Marma
+- name: XLSR Wav2Vec2 Swedish by KBLab
   results:
   - task: 
       name: Speech Recognition
@@ -41,8 +41,8 @@ from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
 
 test_dataset = load_dataset("common_voice", "sv-SE", split="test[:2%]").
 
-processor = Wav2Vec2Processor.from_pretrained("marma/wav2vec2-large-xlsr-swedish")
-model = Wav2Vec2ForCTC.from_pretrained("marma/wav2vec2-large-xlsr-swedish")
+processor = Wav2Vec2Processor.from_pretrained("KBLab/wav2vec2-large-xlsr-53-swedish")
+model = Wav2Vec2ForCTC.from_pretrained("KBLab/wav2vec2-large-xlsr-53-swedish")
 
 resampler = torchaudio.transforms.Resample(48_000, 16_000)
 
@@ -81,8 +81,8 @@ import re
 test_dataset = load_dataset("common_voice", "sv-SE", split="test")
 wer = load_metric("wer")
 
-processor = Wav2Vec2Processor.from_pretrained("marma/wav2vec2-large-xlsr-swedish")
-model = Wav2Vec2ForCTC.from_pretrained("marma/wav2vec2-large-xlsr-swedish")
+processor = Wav2Vec2Processor.from_pretrained("KBLab/wav2vec2-large-xlsr-53-swedish")
+model = Wav2Vec2ForCTC.from_pretrained("KBLab/wav2vec2-large-xlsr-53-swedish")
 model.to("cuda")
 
 chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“]'