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/tmpx6toxjox/bnurpek/gpt2-256t-pos-7")
+generator = pipeline("text-generation", model="bnurpek//tmp/tmp1v9fuz61/bnurpek/gpt2-256t-pos-7")
 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/tmpx6toxjox/bnurpek/gpt2-256t-pos-7")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("bnurpek//tmp/tmpx6toxjox/bnurpek/gpt2-256t-pos-7")
+tokenizer = AutoTokenizer.from_pretrained("bnurpek//tmp/tmp1v9fuz61/bnurpek/gpt2-256t-pos-7")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("bnurpek//tmp/tmp1v9fuz61/bnurpek/gpt2-256t-pos-7")
 
 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 sha256:77d5686a5e539d3c7068e47b4310dfe375b0d1a057ab598f49c64ff34bccb617
+oid sha256:1a31929daa0e3f46108172ed6a814d8b5f9592d49d9bdc3fc78c733085dc5c28
 size 497777468