Update README.md

README.md

@@ -113,17 +113,24 @@ Suggestion 1: 71
 
 If you don’t have access to a larger GPU but want to try the model out, you can run it in a quantized format in Google Colab. **The quality of the responses might deteriorate significantly.** Follow these steps:
 
-### Step 1: Install Dependencies
-```
+### Step 1: Connect to free GPU
+1. Click Connect arrow_drop_down near the top right of the notebook.
+2. Select Change runtime type.
+3. In the modal window, select T4 GPU as your hardware accelerator.
+4. Click Save.
+5. Click the Connect button to connect to your runtime. After some time, the button will present a green checkmark, along with RAM and disk usage graphs. This indicates that a server has successfully been created with your required hardware.
+
+
+### Step 2: Install Dependencies
+
+```python
 !pip install -U bitsandbytes
 import os
 os._exit(00)
 ```
 
-### Step 2: Download and quantize the model
-
+### Step 3: Download and quantize the model
 ```python
-
 from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, pipeline
 import torch
 
@@ -145,8 +152,8 @@ generation_pipeline = pipeline(
     device_map="auto",
 )
 ```
-### Step 3: Run inference on a papyrus fragment of your choice
-```
+### Step 4: Run inference on a papyrus fragment of your choice
+```python
 # This is a rough transcription of Pap.Ups. 106
 papyrus_edition = """
 ετουσ τεταρτου αυτοκρατοροσ καισαροσ ουεσπασιανου σεβαστου ------------------