Update README.md

README.md

@@ -97,8 +97,8 @@ Pile-T5 can be loaded using the `AutoModelForSeq2SeqLM` functionality:
 ```python
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-tokenizer = AutoTokenizer.from_pretrained("EleutherAI/pile-t5-base")
-model = AutoModelForSeq2SeqLM.from_pretrained("EleutherAI/pile-t5-base")
+tokenizer = AutoTokenizer.from_pretrained("EleutherAI/pile-t5-large")
+model = AutoModelForSeq2SeqLM.from_pretrained("EleutherAI/pile-t5-large")
 ```
 
 ### Training
@@ -131,6 +131,7 @@ Intermediate checkpoints for Pile-T5 are accessible within this repository.
 There are in total 200 checkpoints that are spaced 10,000 steps. For T5x-native
 checkpoints that can be used for finetuning with the T5x library, refer to [here](https://huggingface.co/lintang/pile-t5-base-t5x/tree/main)
 
+The training loss (in tfevent format) and validation perplexity (in jsonl) can be found [here](https://huggingface.co/EleutherAI/pile-t5-large/blob/main/large.zip).
 
 ### Evaluations