Push model using huggingface_hub.

README.md

@@ -26,7 +26,7 @@ You can then generate text as follows:
 ```python
 from transformers import pipeline
 
-generator = pipeline("text-generation", model="jvelja//tmp/tmpdy3yyo0o/jvelja/vllm-gemma2b-stringMatcher-newDataset_3")
+generator = pipeline("text-generation", model="jvelja//tmp/tmpwld9quos/jvelja/vllm-gemma2b-stringMatcher-newDataset_3")
 outputs = generator("Hello, my llama is cute")
 ```
 
@@ -36,8 +36,8 @@ 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("jvelja//tmp/tmpdy3yyo0o/jvelja/vllm-gemma2b-stringMatcher-newDataset_3")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("jvelja//tmp/tmpdy3yyo0o/jvelja/vllm-gemma2b-stringMatcher-newDataset_3")
+tokenizer = AutoTokenizer.from_pretrained("jvelja//tmp/tmpwld9quos/jvelja/vllm-gemma2b-stringMatcher-newDataset_3")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("jvelja//tmp/tmpwld9quos/jvelja/vllm-gemma2b-stringMatcher-newDataset_3")
 
 inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
 outputs = model(**inputs, labels=inputs["input_ids"])

adapter_model.safetensors

@@ -1,3 +1,3 @@
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 size 12793376

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:b7fb6725ca03988fb3156a419ad1205110ab3c58ca493649d8e5b92fca0b8155
 size 10748