Update README.md

README.md

@@ -19,3 +19,23 @@ The following `bitsandbytes` quantization config was used during training:
 
 
 - PEFT 0.5.0
+
+## Get it started
+```python
+from peft import PeftModel, PeftConfig
+from huggingface_hub import login
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+login("[YOUR HF TOKEN HERE FOR USING LLAMA]")
+config = PeftConfig.from_pretrained("ChangeIsKey/llama-7b-lexical-substitution")
+base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf")
+
+tokenizer = AutoTokenizer.from_pretrained(base_model_name, use_fast=False, trust_remote_code=True, cache_dir=LLMs_CACHE_DIR)
+tokenizer.add_special_tokens({ "additional_special_tokens":[AddedToken("<|s|>"), AddedToken("<|answer|>"), AddedToken("<|end|>")]})
+if tokenizer.pad_token is None:
+    tokenizer.add_special_tokens({'pad_token': '[PAD]'})
+tokenizer.padding_side = 'left'
+base_model.resize_token_embeddings(len(tokenizer))
+
+model = PeftModel.from_pretrained(base_model, "ChangeIsKey/llama-7b-lexical-substitution")
+```