Update README.md

README.md

@@ -13,38 +13,4 @@ widget:
 * pre-processing: normalization + SentencePiece
 * test set scores: syllable: 15.95, word: 8.43
 
-## Training
-
-Training scripts from [LalitaDeelert/NLP-ZH_TH-Project](https://github.com/LalitaDeelert/NLP-ZH_TH-Project). Experiments tracked at [cstorm125/marianmt-zh_cn-th](https://wandb.ai/cstorm125/marianmt-zh_cn-th).
-
-```
-export WANDB_PROJECT=marianmt-zh_cn-th
-python train_model.py --input_fname ../data/v1/Train.csv \\\\\\\\\\\\\\\\
-\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\t--output_dir ../models/marianmt-zh_cn-th \\\\\\\\\\\\\\\\
-\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\t--source_lang zh --target_lang th \\\\\\\\\\\\\\\\
-\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\t--metric_tokenize th_syllable --fp16 
-```
-
-## Usage
-
-```
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
- 
-tokenizer = AutoTokenizer.from_pretrained("Lalita/marianmt-zh_cn-th")
-model = AutoModelForSeq2SeqLM.from_pretrained("Lalita/marianmt-zh_cn-th").cpu()
-
-src_text = [
-    '我爱你',
-    '我想吃米饭',
-]
-translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
-print([tokenizer.decode(t, skip_special_tokens=True) for t in translated])
-
-> ['ผมรักคุณนะ', 'ฉันอยากกินข้าว']
-```
-
-## Requirements
-```
-transformers==4.6.0
-torch==1.8.0
-```
+#