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="yuchiz//srv/condor/execute/dir_42917/tmphks533ao/yuchiz/cache")
+generator = pipeline("text-generation", model="yuchiz//srv/condor/execute/dir_42917/tmp0j4dyijv/yuchiz/cache")
 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("yuchiz//srv/condor/execute/dir_42917/tmphks533ao/yuchiz/cache")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("yuchiz//srv/condor/execute/dir_42917/tmphks533ao/yuchiz/cache")
+tokenizer = AutoTokenizer.from_pretrained("yuchiz//srv/condor/execute/dir_42917/tmp0j4dyijv/yuchiz/cache")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("yuchiz//srv/condor/execute/dir_42917/tmp0j4dyijv/yuchiz/cache")
 
 inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
 outputs = model(**inputs, labels=inputs["input_ids"])

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2c4a75e5f351249299075bf932e1155bf75f7f841055a51fb6dc9a78abfa5bc8
+oid sha256:4a91e64292b7554baf11a4410972e20fab7bc609924efc5a8a657d3ebcecff43
 size 17471