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/tmpawsh_b1x/bnurpek/gpt2-256T-neg-5")
+generator = pipeline("text-generation", model="bnurpek//tmp/tmp760_t4fi/bnurpek/gpt2-256T-neg-5")
 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/tmpawsh_b1x/bnurpek/gpt2-256T-neg-5")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("bnurpek//tmp/tmpawsh_b1x/bnurpek/gpt2-256T-neg-5")
+tokenizer = AutoTokenizer.from_pretrained("bnurpek//tmp/tmp760_t4fi/bnurpek/gpt2-256T-neg-5")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("bnurpek//tmp/tmp760_t4fi/bnurpek/gpt2-256T-neg-5")
 
 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:fc0f8ec179304bf23a2644938d3b9344fc828a9c416248be9993c42680669f9a
+oid sha256:e4e562dfde89d3a9ed6113c9c9bd84ca4fb57d0188e11924f7ba647f9d610490
 size 497777468