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="amirabdullah19852020//tmp/tmpon_jafxi/amirabdullah19852020/gpt-neo-125m_sentiment_reward")
+generator = pipeline("text-generation", model="amirabdullah19852020//tmp/tmpfui0udca/amirabdullah19852020/gpt-neo-125m_sentiment_reward")
 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("amirabdullah19852020//tmp/tmpon_jafxi/amirabdullah19852020/gpt-neo-125m_sentiment_reward")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("amirabdullah19852020//tmp/tmpon_jafxi/amirabdullah19852020/gpt-neo-125m_sentiment_reward")
+tokenizer = AutoTokenizer.from_pretrained("amirabdullah19852020//tmp/tmpfui0udca/amirabdullah19852020/gpt-neo-125m_sentiment_reward")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("amirabdullah19852020//tmp/tmpfui0udca/amirabdullah19852020/gpt-neo-125m_sentiment_reward")
 
 inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
 outputs = model(**inputs, labels=inputs["input_ids"])