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/tmpsisbc64t/SummerSigh/T5-Base-Rule-Of-Thumb-RM2")
+generator = pipeline("text-generation", model="SummerSigh//tmp/tmpt3bcykb9/SummerSigh/T5-Base-Rule-Of-Thumb-RM2")
 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/tmpsisbc64t/SummerSigh/T5-Base-Rule-Of-Thumb-RM2")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("SummerSigh//tmp/tmpsisbc64t/SummerSigh/T5-Base-Rule-Of-Thumb-RM2")
+tokenizer = AutoTokenizer.from_pretrained("SummerSigh//tmp/tmpt3bcykb9/SummerSigh/T5-Base-Rule-Of-Thumb-RM2")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("SummerSigh//tmp/tmpt3bcykb9/SummerSigh/T5-Base-Rule-Of-Thumb-RM2")
 
 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:dfa8174d4b230fe9106edadaec6a729f5829e0a5810117f64a1a23cefc9bc2e6
+oid sha256:ceee8295092e72c420a983e380b12d174a0032fa34202a83760d20564fccafa8
 size 990412605