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="dshin//tmp/tmp1i0a_ffs/dshin/flan-t5-ppo-user-a-allenai-prosocial-dialog")
+generator = pipeline("text-generation", model="dshin//tmp/tmpw0kwbx78/dshin/flan-t5-ppo-user-a-allenai-prosocial-dialog")
 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("dshin//tmp/tmp1i0a_ffs/dshin/flan-t5-ppo-user-a-allenai-prosocial-dialog")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("dshin//tmp/tmp1i0a_ffs/dshin/flan-t5-ppo-user-a-allenai-prosocial-dialog")
+tokenizer = AutoTokenizer.from_pretrained("dshin//tmp/tmpw0kwbx78/dshin/flan-t5-ppo-user-a-allenai-prosocial-dialog")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("dshin//tmp/tmpw0kwbx78/dshin/flan-t5-ppo-user-a-allenai-prosocial-dialog")
 
 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 sha256:9b1ccae91afbb8b649ce29804ddc03ee15b2a2f5e3a78630e61e69b62c6ec309
+oid sha256:31d5e705846ab49aa8a631cb4115fdf17d4a98477d1062ae0ecf66e3abe83a58
 size 990412605