Update README.md

README.md

@@ -12,13 +12,11 @@ datasets:
 - ARTeLab/mlsum-it
 ---
 
-<!-- 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. -->
-
 # summarization_mlsum
 
-This model is a fine-tuned version of [gsarti/it5-base](https://huggingface.co/gsarti/it5-base) on an unknown dataset.
-It achieves the following results on the evaluation set:
+This model is a fine-tuned version of [gsarti/it5-base](https://huggingface.co/gsarti/it5-base) on MLSum-it for Abstractive Summarization.
+
+It achieves the following results:
 - Loss: 2.0190
 - Rouge1: 19.2854
 - Rouge2: 6.0392
@@ -26,19 +24,12 @@ It achieves the following results on the evaluation set:
 - Rougelsum: 16.616
 - Gen Len: 32.7635
 
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
+## Usage 
+```python
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+tokenizer = T5Tokenizer.from_pretrained("ARTeLab/it5-summarization-mlsum")
+model = T5ForConditionalGeneration.from_pretrained("ARTeLab/it5-summarization-mlsum")
+```
 
 ### Training hyperparameters
 
@@ -51,13 +42,9 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 4.0
 
-### Training results
-
-
-
 ### Framework versions
 
 - Transformers 4.12.0.dev0
 - Pytorch 1.9.1+cu102
 - Datasets 1.12.1
-- Tokenizers 0.10.3
+- Tokenizers 0.10.3