Update README.md

README.md

@@ -15,7 +15,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 # flan-t5-large-spelling-peft
 
-This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset.
+This model is an *experimental* peft adapter for [google/flan-t5-large](https://huggingface.co/google/flan-t5-large)
+trained on the `wiki.en` dataset from [oliverguhr/spelling](https://github.com/oliverguhr/spelling).
+
 It achieves the following results on the evaluation set:
 - Loss: 0.2537
 - Rouge1: 95.8905
@@ -26,15 +28,38 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This an experimental model that should be capable of fixing typos and punctuation.
+
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, pipeline
+
+```python
+model_id = "google/flan-t5-large"
+peft_model_id = "jbochi/flan-t5-large-spelling-peft"
+
+model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
+model.load_adapter(peft_model_id)
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+pipe = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
+pipe("Fix spelling: This restuarant is awesome")
+# [{'generated_text': 'This restaurant is awesome'}]
+```
 
 ## Intended uses & limitations
 
-More information needed
+Intented for research purposes.
+
+- It may produce artifacts.
+- Doesn't seen capable of fixing multiple errors in a single sentence.
+- It doesn't support languages other than English.
+- It was fine-tuned with a `max_length` of 100 tokens.
 
 ## Training and evaluation data
 
-More information needed
+Data from [oliverguhr/spelling](https://github.com/oliverguhr/spelling), with a "Fix spelling: " prefix added to every example.
+
+The model was only evaluated on the first 100 test examples only during training.
 
 ## Training procedure