Update readme with usage instructions.

README.md

@@ -5,4 +5,45 @@ datasets:
 language:
 - en
 library_name: transformers
----
+---
+# Generate SQL from text - Squeal
+
+
+Please use the code below as an example for how to use this model.
+
+This model was streamed on Youtube.
+
+https://www.youtube.com/watch?v=PNFhAfxR_d8
+
+```python
+import torch
+from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+
+def load_model(model_name):
+    # Load tokenizer and model with QLoRA configuration
+    compute_dtype = getattr(torch, 'float16')
+
+    bnb_config = BitsAndBytesConfig(
+        load_in_4bit=True,
+        bnb_4bit_quant_type='nf4',
+        bnb_4bit_compute_dtype=compute_dtype,
+        bnb_4bit_use_double_quant=False,
+    )
+
+    model = AutoModelForCausalLM.from_pretrained(
+        model_name,
+        device_map={"": 0},
+        quantization_config=bnb_config
+    )
+
+
+    # Load Tokenizer
+    tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+    tokenizer.pad_token = tokenizer.eos_token
+    tokenizer.padding_side = "right"
+
+    return model, tokenizer
+
+model, tokenizer = load_model('vagmi/squeal')
+```
+