Update README.md

README.md

@@ -30,82 +30,6 @@ model-index:
       name: Wer
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+CT2 Model. convert from
 
-# Whisper Medium (Thai): Combined V3
-
-This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on augmented versions of the mozilla-foundation/common_voice_13_0 th, google/fleurs, and curated datasets.
-It achieves the following results on the common-voice-13 test set:
-- WER: 7.42 (with Deepcut Tokenizer)
-
-## Model description
-
-Use the model with huggingface's `transformers` as follows:
-
-```py
-from transformers import pipeline
-
-MODEL_NAME = "biodatlab/whisper-th-medium-combined"  # specify the model name
-lang = "th"  # change to Thai langauge
-
-device = 0 if torch.cuda.is_available() else "cpu"
-
-pipe = pipeline(
-    task="automatic-speech-recognition",
-    model=MODEL_NAME,
-    chunk_length_s=30,
-    device=device,
-)
-pipe.model.config.forced_decoder_ids = pipe.tokenizer.get_decoder_prompt_ids(
-  language=lang,
-  task="transcribe"
-)
-text = pipe("audio.mp3")["text"] # give audio mp3 and transcribe text
-```
-
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 1e-05
-- train_batch_size: 16
-- eval_batch_size: 16
-- seed: 42
-- optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 500
-- training_steps: 10000
-- mixed_precision_training: Native AMP
-
-### Framework versions
-
-- Transformers 4.37.2
-- Pytorch 2.1.0
-- Datasets 2.16.1
-- Tokenizers 0.15.1
-
-## Citation
-
-Cite using Bibtex:
-
-```
-@misc {thonburian_whisper_med,
-    author       = { Atirut Boribalburephan, Zaw Htet Aung, Knot Pipatsrisawat, Titipat Achakulvisut },
-    title        = { Thonburian Whisper: A fine-tuned Whisper model for Thai automatic speech recognition },
-    year         = 2022,
-    url          = { https://huggingface.co/biodatlab/whisper-th-medium-combined },
-    doi          = { 10.57967/hf/0226 },
-    publisher    = { Hugging Face }
-}
-```
+https://huggingface.co/biodatlab/whisper-th-medium-combined