Push model using huggingface_hub.

README.md

@@ -25,7 +25,7 @@ You can then generate text as follows:
 ```python
 from transformers import pipeline
 
-generator = pipeline("text-generation", model="PranavBP525//tmp/tmprl8sf9pk/PranavBP525/phi-2-storygen-rlhf")
+generator = pipeline("text-generation", model="PranavBP525//tmp/tmp44w1s9gw/PranavBP525/phi-2-storygen-rlhf")
 outputs = generator("Hello, my llama is cute")
 ```
 
@@ -35,8 +35,8 @@ 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("PranavBP525//tmp/tmprl8sf9pk/PranavBP525/phi-2-storygen-rlhf")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("PranavBP525//tmp/tmprl8sf9pk/PranavBP525/phi-2-storygen-rlhf")
+tokenizer = AutoTokenizer.from_pretrained("PranavBP525//tmp/tmp44w1s9gw/PranavBP525/phi-2-storygen-rlhf")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("PranavBP525//tmp/tmp44w1s9gw/PranavBP525/phi-2-storygen-rlhf")
 
 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 sha256:20430e8538a76dfb9d62981ab5a89bdbbda76cb0cbc69948a790ba845edec0d5
+oid sha256:06510d5f1a961ccb3e6f550fd88f45197532616899b5a3e4d0ea40fbe6df1dde
 size 11772