diff --git a/Home.md b/Home.md
index 9a7d291..a1fd792 100644
--- a/Home.md
+++ b/Home.md
@@ -66,4 +66,38 @@ TrainingArguments(
     eval_steps = 1,
 )
 ```
-This will cause no OOMs and make it somewhat faster with no upcasting to float32.
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+This will cause no OOMs and make it somewhat faster with no upcasting to float32.
+
+### GGUF quantization options
+```python
+# https://github.com/ggerganov/llama.cpp/blob/master/examples/quantize/quantize.cpp#L19
+# From https://mlabonne.github.io/blog/posts/Quantize_Llama_2_models_using_ggml.html
+ALLOWED_QUANTS = \
+{
+    "not_quantized"  : "Recommended. Fast conversion. Slow inference, big files.",
+    "fast_quantized" : "Recommended. Fast conversion. OK inference, OK file size.",
+    "quantized"      : "Recommended. Slow conversion. Fast inference, small files.",
+    "f32"     : "Not recommended. Retains 100% accuracy, but super slow and memory hungry.",
+    "f16"     : "Fastest conversion + retains 100% accuracy. Slow and memory hungry.",
+    "q8_0"    : "Fast conversion. High resource use, but generally acceptable.",
+    "q4_k_m"  : "Recommended. Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q4_K",
+    "q5_k_m"  : "Recommended. Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q5_K",
+    "q2_k"    : "Uses Q4_K for the attention.vw and feed_forward.w2 tensors, Q2_K for the other tensors.",
+    "q3_k_l"  : "Uses Q5_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K",
+    "q3_k_m"  : "Uses Q4_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K",
+    "q3_k_s"  : "Uses Q3_K for all tensors",
+    "q4_0"    : "Original quant method, 4-bit.",
+    "q4_1"    : "Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models.",
+    "q4_k_s"  : "Uses Q4_K for all tensors",
+    "q4_k"    : "alias for q4_k_m",
+    "q5_k"    : "alias for q5_k_m",
+    "q5_0"    : "Higher accuracy, higher resource usage and slower inference.",
+    "q5_1"    : "Even higher accuracy, resource usage and slower inference.",
+    "q5_k_s"  : "Uses Q5_K for all tensors",
+    "q6_k"    : "Uses Q8_K for all tensors",
+    "iq2_xxs" : "2.06 bpw quantization",
+    "iq2_xs"  : "2.31 bpw quantization",
+    "iq3_xxs" : "3.06 bpw quantization",
+    "q3_k_xs" : "3-bit extra small quantization",
+}
+```
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