try again with large one

main.py

@@ -16,9 +16,10 @@ from transformers import T5Tokenizer, T5ForConditionalGeneration
 # model = AutoModelForSeq2SeqLM.from_pretrained("facebook/blenderbot-1B-distill")
 # tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-small")
 # model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-small")
-tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-base")
-model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base")
-
+# tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-base")
+# model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base")
+tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-large")
+model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large")
 
 token_size_limit = 128
 

tutorial.md

@@ -28,3 +28,11 @@ Use the embedded address, for example:
 ```bash
 curl -X POST https://chihchiu29-mychatbot.hf.space/reply -H 'Content-Type: application/json' -d '{"msg": "hi"}'
 ```
+
+## Remove dangling images
+
+From: https://github.com/fabric8io/docker-maven-plugin/issues/501
+
+```bash
+docker rmi $(docker images -qa -f 'dangling=true')
+```