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/tmpvv7548qb/SummerSigh/T5-Base-Rule-Of-Thumb-RM")
+generator = pipeline("text-generation", model="SummerSigh//tmp/tmp0785c2gc/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/tmpvv7548qb/SummerSigh/T5-Base-Rule-Of-Thumb-RM")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("SummerSigh//tmp/tmpvv7548qb/SummerSigh/T5-Base-Rule-Of-Thumb-RM")
+tokenizer = AutoTokenizer.from_pretrained("SummerSigh//tmp/tmp0785c2gc/SummerSigh/T5-Base-Rule-Of-Thumb-RM")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("SummerSigh//tmp/tmp0785c2gc/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 @@
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+oid sha256:2823cce89fd6fb4a642f7171d1e6e3a00c56a280dfe4f9f7816a94e13c4e8668
 size 990412605

spiece.model

@@ -0,0 +1,3 @@
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+size 791656