Push model using huggingface_hub.

README.md

@@ -25,7 +25,7 @@ You can then generate text as follows:
 ```python
 from transformers import pipeline
 
-generator = pipeline("text-generation", model="bnurpek//tmp/tmplnkpke85/bnurpek/try2-gpt2-256T-neg-3")
+generator = pipeline("text-generation", model="bnurpek//tmp/tmphqhmvrew/bnurpek/try2-gpt2-256T-neg-3")
 outputs = generator("Hello, my llama is cute")
 ```
 
@@ -35,8 +35,8 @@ 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("bnurpek//tmp/tmplnkpke85/bnurpek/try2-gpt2-256T-neg-3")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("bnurpek//tmp/tmplnkpke85/bnurpek/try2-gpt2-256T-neg-3")
+tokenizer = AutoTokenizer.from_pretrained("bnurpek//tmp/tmphqhmvrew/bnurpek/try2-gpt2-256T-neg-3")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("bnurpek//tmp/tmphqhmvrew/bnurpek/try2-gpt2-256T-neg-3")
 
 inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
 outputs = model(**inputs, labels=inputs["input_ids"])

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6893a3fa555c867a79207b437cb0048f44a891947c95bebb4575326776522bb4
+oid sha256:347397095ff884bf9f737b59e79f182d9b5ed675e4012fb3f0dba8ccfe113139
 size 497777468