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/tmp9d54agxs/Evan-Lin/Bart-abs-yelp-entailment")
+generator = pipeline("text-generation", model="Evan-Lin//tmp/tmps_u5v_y3/Evan-Lin/Bart-abs-yelp-allure-10")
 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/tmp9d54agxs/Evan-Lin/Bart-abs-yelp-entailment")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("Evan-Lin//tmp/tmp9d54agxs/Evan-Lin/Bart-abs-yelp-entailment")
+tokenizer = AutoTokenizer.from_pretrained("Evan-Lin//tmp/tmps_u5v_y3/Evan-Lin/Bart-abs-yelp-allure-10")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("Evan-Lin//tmp/tmps_u5v_y3/Evan-Lin/Bart-abs-yelp-allure-10")
 
 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:b615fb6e07d3c3e1661f1473de78fb73ae8330edec71b631d82920e84aa04c8b
+oid sha256:0fcb3df76fcd7e1ac0368cceb5b1da1f4f8139589e70f9c680dd06d512a4350a
 size 557974885