Push model using huggingface_hub.

README.md

@@ -24,7 +24,7 @@ You can then generate text as follows:
 ```python
 from transformers import pipeline
 
-generator = pipeline("text-generation", model="Evan-Lin//tmp/tmpxxfkrucb/Evan-Lin/Bart-large-abs-yelp-allure2")
+generator = pipeline("text-generation", model="Evan-Lin//tmp/tmpf0oirlmn/Evan-Lin/Bart-large-abs-yelp-allure2")
 outputs = generator("Hello, my llama is cute")
 ```
 
@@ -34,8 +34,8 @@ If you want to use the model for training or to obtain the outputs from the valu
 from transformers import AutoTokenizer
 from trl import AutoModelForCausalLMWithValueHead
 
-tokenizer = AutoTokenizer.from_pretrained("Evan-Lin//tmp/tmpxxfkrucb/Evan-Lin/Bart-large-abs-yelp-allure2")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("Evan-Lin//tmp/tmpxxfkrucb/Evan-Lin/Bart-large-abs-yelp-allure2")
+tokenizer = AutoTokenizer.from_pretrained("Evan-Lin//tmp/tmpf0oirlmn/Evan-Lin/Bart-large-abs-yelp-allure2")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("Evan-Lin//tmp/tmpf0oirlmn/Evan-Lin/Bart-large-abs-yelp-allure2")
 
 inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
 outputs = model(**inputs, labels=inputs["input_ids"])

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:198529ccce3f4bbd03eb001251c50c118f1dc8999930f0c927e5ac0a453ed384
+oid sha256:ea3abaf01a821daadc70f3d68348757c4723537a6ade1d392db0b3df71b9e111
 size 1625546133