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="SummerSigh//tmp/tmpqfm_25bg/SummerSigh/T5-Base-Rule-Of-Thumb-RM")
+generator = pipeline("text-generation", model="SummerSigh//tmp/tmpvv7548qb/SummerSigh/T5-Base-Rule-Of-Thumb-RM")
 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("SummerSigh//tmp/tmpqfm_25bg/SummerSigh/T5-Base-Rule-Of-Thumb-RM")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("SummerSigh//tmp/tmpqfm_25bg/SummerSigh/T5-Base-Rule-Of-Thumb-RM")
+tokenizer = AutoTokenizer.from_pretrained("SummerSigh//tmp/tmpvv7548qb/SummerSigh/T5-Base-Rule-Of-Thumb-RM")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("SummerSigh//tmp/tmpvv7548qb/SummerSigh/T5-Base-Rule-Of-Thumb-RM")
 
 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 sha256:3bc0a19a420d4b884eb79ffee129869a1522c34470e9d3155a076eb4b61b3784
+oid sha256:db2ff397e9ca28ead3dacb99b553b44d2053ee396805df3b0081c84701d3862c
 size 990412605