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/tmp4lgp7cjq/amirabdullah19852020/pythia_70m_ppo_imdb_sentiment_with_checkpoints")
+generator = pipeline("text-generation", model="amirabdullah19852020//tmp/tmpvqhw4_hp/amirabdullah19852020/pythia_70m_ppo_imdb_sentiment_with_checkpoints")
 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/tmp4lgp7cjq/amirabdullah19852020/pythia_70m_ppo_imdb_sentiment_with_checkpoints")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("amirabdullah19852020//tmp/tmp4lgp7cjq/amirabdullah19852020/pythia_70m_ppo_imdb_sentiment_with_checkpoints")
+tokenizer = AutoTokenizer.from_pretrained("amirabdullah19852020//tmp/tmpvqhw4_hp/amirabdullah19852020/pythia_70m_ppo_imdb_sentiment_with_checkpoints")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("amirabdullah19852020//tmp/tmpvqhw4_hp/amirabdullah19852020/pythia_70m_ppo_imdb_sentiment_with_checkpoints")
 
 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:a654b266d7d1857f5e60cc2e8ff1d9c405ddb80cdd1d577a68b4ce11673588f0
+oid sha256:46461a3b01fa284ccb08283160031e9fd3e49a667aec979ca4d7737d88fa82d1
 size 306795729