docs: usage

README.md

@@ -3,4 +3,32 @@ datasets:
 - liweili/c4_200m
 language:
 - en
----
+---
+
+```python
+# Load model directly
+import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+torch_device = 'cuda' if torch.cuda.is_available() else 'cpu'
+
+tokenizer = AutoTokenizer.from_pretrained("thenHung/english-grammar-error-correction-t5-seq2seq")
+model = AutoModelForSeq2SeqLM.from_pretrained("thenHung/english-grammar-error-correction-t5-seq2seq").to(torch_device)
+
+
+def correct_grammar(input_text,num_return_sequences):
+  batch = tokenizer([input_text],truncation=True,padding='max_length',max_length=64, return_tensors="pt").to(torch_device)
+  translated = model.generate(**batch,max_length=64,num_beams=4, num_return_sequences=num_return_sequences, temperature=1.5)
+  tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)
+  return tgt_text
+
+input_text = """
+He are an teachers.
+"""
+num_return_sequences = 3
+corrected_texts = correct_grammar(input_text, num_return_sequences)
+print(corrected_texts)
+
+# output:
+# ['He is a teacher.', 'He is an educator.', 'He is one of the teachers.']
+```