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="XanderJC//tmp/tmpn4ksj9no/XanderJC/llama-3-8b-orca-abc")
+generator = pipeline("text-generation", model="XanderJC//tmp/tmpzvcma_9l/XanderJC/llama-3-8b-orca-abc")
 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("XanderJC//tmp/tmpn4ksj9no/XanderJC/llama-3-8b-orca-abc")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("XanderJC//tmp/tmpn4ksj9no/XanderJC/llama-3-8b-orca-abc")
+tokenizer = AutoTokenizer.from_pretrained("XanderJC//tmp/tmpzvcma_9l/XanderJC/llama-3-8b-orca-abc")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("XanderJC//tmp/tmpzvcma_9l/XanderJC/llama-3-8b-orca-abc")
 
 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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+oid sha256:a50e4debf7a2b1df182c5808e063ce245310df84a1f3dd4724db3bc1b8150b7a
 size 54543184

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:00199708139b5be353dc689d7d8a6b878336eabe871a5dbff994688fecf432bd
 size 17916