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/tmpn8nky8x7/SummerSigh/T5-Base-EvilPrompterRM")
+generator = pipeline("text-generation", model="SummerSigh//tmp/tmp_wiiw7_h/SummerSigh/T5-Base-EvilPrompterRM")
 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/tmpn8nky8x7/SummerSigh/T5-Base-EvilPrompterRM")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("SummerSigh//tmp/tmpn8nky8x7/SummerSigh/T5-Base-EvilPrompterRM")
+tokenizer = AutoTokenizer.from_pretrained("SummerSigh//tmp/tmp_wiiw7_h/SummerSigh/T5-Base-EvilPrompterRM")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("SummerSigh//tmp/tmp_wiiw7_h/SummerSigh/T5-Base-EvilPrompterRM")
 
 inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
 outputs = model(**inputs, labels=inputs["input_ids"])

config.json

@@ -55,7 +55,7 @@
   },
   "tie_word_embeddings": false,
   "torch_dtype": "float32",
-  "transformers_version": "4.26.1",
+  "transformers_version": "4.22.1",
   "use_cache": true,
   "vocab_size": 32128
 }

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5196d0d013c64c61ef15378ad7654d30e26110ef14736759c28d437432e0f546
+oid sha256:29334ac025438de4e674f37a2e4a6e30e242ad44786c43e6f54fc51a20c29250
 size 990412605