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/tmpabu3zwc3/yuchiz/cache")
+generator = pipeline("text-generation", model="yuchiz//srv/condor/execute/dir_42917/tmpq5ou7bos/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/tmpabu3zwc3/yuchiz/cache")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("yuchiz//srv/condor/execute/dir_42917/tmpabu3zwc3/yuchiz/cache")
+tokenizer = AutoTokenizer.from_pretrained("yuchiz//srv/condor/execute/dir_42917/tmpq5ou7bos/yuchiz/cache")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("yuchiz//srv/condor/execute/dir_42917/tmpq5ou7bos/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 sha256:95a9125b8a5f799e15ea02a4b5d3a75cb1fb353bda639eba0e3742868a7a4c8e
+oid sha256:10796dc9d25ab3e13ba911bf6ab83581bf37489db98a05e0a5f7a9a595b9e898
 size 17471