feat/llama-2 examples (#319)

* qlora llama-2

* qlora llama-2

* linting

* readme

* lora added

* linting

* change group_by_length

* 13b fitting on 24gb

* grouped lengths true

* add pad token

* change out dir

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Co-authored-by: Mads Henrichsen <mads@Brbar-tilhrende-Mads.local>

examples/llama-2/README.md

@@ -0,0 +1,20 @@
+# Overview
+
+This is an example of a llama-2 configuration for 7b and 13b. The yaml file contains configuration for the 7b variant, but you can just aswell use the same settings for 13b.
+
+The 7b variant fits on any 24GB VRAM GPU and will take up about 17 GB of VRAM during training if using qlora and 20 GB if using lora. On a RTX 4090 it trains 3 epochs of the default dataset in about 15 minutes.
+
+The 13b variant will fit if you change these settings to these values:
+gradient_accumulation_steps: 2
+micro_batch_size: 1
+
+```shell
+accelerate launch scripts/finetune.py examples/llama-2/qlora.yml
+
+```
+or
+
+```shell
+accelerate launch scripts/finetune.py examples/llama-2/lora.yml
+
+```