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/tmpls4jm05k/jvelja/vllm-gemma2b-stringMatcher-newDataset_1")
+generator = pipeline("text-generation", model="jvelja//tmp/tmpiicii66o/jvelja/vllm-gemma2b-stringMatcher-newDataset_1")
 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/tmpls4jm05k/jvelja/vllm-gemma2b-stringMatcher-newDataset_1")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("jvelja//tmp/tmpls4jm05k/jvelja/vllm-gemma2b-stringMatcher-newDataset_1")
+tokenizer = AutoTokenizer.from_pretrained("jvelja//tmp/tmpiicii66o/jvelja/vllm-gemma2b-stringMatcher-newDataset_1")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("jvelja//tmp/tmpiicii66o/jvelja/vllm-gemma2b-stringMatcher-newDataset_1")
 
 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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 size 10748