Update README.md

README.md

@@ -3,8 +3,37 @@ library_name: peft
 tags:
 - text-generation
 ---
-## Training procedure
+## QLoRA weights using Llama-2-7b for the Code Alpaca Dataset
+
+This model was fine-tuned using [Predibase](https://predibase.com/), the first low-code AI platform for engineers.
+I fine-tuned base Llama-2-7b using LoRA with 4 bit quantization on a single T4 GPU.
+
+Dataset: https://github.com/sahil280114/codealpaca
+
+To use these weights:
+```
+from peft import PeftModel, PeftConfig
+from transformers import AutoModelForCausalLM
+
+config = PeftConfig.from_pretrained("arnavgrg/codealpaca-qlora")
+model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf")
+model = PeftModel.from_pretrained(model, "arnavgrg/codealpaca-qlora")
+```
+
+Prompt Template:
+```
+Below is an instruction that describes a task, paired with an input
+that provides further context. Write a response that appropriately
+completes the request.
 
+### Instruction: {instruction}
+
+### Input: {input}
+
+### Response:
+```
+
+## Training procedure
 
 The following `bitsandbytes` quantization config was used during training:
 - load_in_8bit: False
@@ -16,6 +45,7 @@ The following `bitsandbytes` quantization config was used during training:
 - bnb_4bit_quant_type: nf4
 - bnb_4bit_use_double_quant: True
 - bnb_4bit_compute_dtype: float16
+
 ### Framework versions