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README.md

@@ -110,18 +110,18 @@ Refer to the Provided Files table below to see what files use which methods, and
 
 | Name | Quant method | Bits | Size | Max RAM required | Use case |
 | ---- | ---- | ---- | ---- | ---- | ----- |
-| [airoboros-l2-7b.Q2_K.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b.Q2_K.gguf) | Q2_K | 2 | 2.83 GB| 5.33 GB | smallest, significant quality loss - not recommended for most purposes |
-| [airoboros-l2-7b.Q3_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b.Q3_K_S.gguf) | Q3_K_S | 3 | 2.95 GB| 5.45 GB | very small, high quality loss |
-| [airoboros-l2-7b.Q3_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b.Q3_K_M.gguf) | Q3_K_M | 3 | 3.30 GB| 5.80 GB | very small, high quality loss |
-| [airoboros-l2-7b.Q3_K_L.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b.Q3_K_L.gguf) | Q3_K_L | 3 | 3.60 GB| 6.10 GB | small, substantial quality loss |
-| [airoboros-l2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b.Q4_0.gguf) | Q4_0 | 4 | 3.83 GB| 6.33 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
-| [airoboros-l2-7b.Q4_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b.Q4_K_S.gguf) | Q4_K_S | 4 | 3.86 GB| 6.36 GB | small, greater quality loss |
-| [airoboros-l2-7b.Q4_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b.Q4_K_M.gguf) | Q4_K_M | 4 | 4.08 GB| 6.58 GB | medium, balanced quality - recommended |
-| [airoboros-l2-7b.Q5_0.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b.Q5_0.gguf) | Q5_0 | 5 | 4.65 GB| 7.15 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
-| [airoboros-l2-7b.Q5_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b.Q5_K_S.gguf) | Q5_K_S | 5 | 4.65 GB| 7.15 GB | large, low quality loss - recommended |
-| [airoboros-l2-7b.Q5_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b.Q5_K_M.gguf) | Q5_K_M | 5 | 4.78 GB| 7.28 GB | large, very low quality loss - recommended |
-| [airoboros-l2-7b.Q6_K.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b.Q6_K.gguf) | Q6_K | 6 | 5.53 GB| 8.03 GB | very large, extremely low quality loss |
-| [airoboros-l2-7b.Q8_0.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b.Q8_0.gguf) | Q8_0 | 8 | 7.16 GB| 9.66 GB | very large, extremely low quality loss - not recommended |
+| [airoboros-l2-7b-2.2.Q2_K.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b-2.2.Q2_K.gguf) | Q2_K | 2 | 2.83 GB| 5.33 GB | smallest, significant quality loss - not recommended for most purposes |
+| [airoboros-l2-7b-2.2.Q3_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b-2.2.Q3_K_S.gguf) | Q3_K_S | 3 | 2.95 GB| 5.45 GB | very small, high quality loss |
+| [airoboros-l2-7b-2.2.Q3_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b-2.2.Q3_K_M.gguf) | Q3_K_M | 3 | 3.30 GB| 5.80 GB | very small, high quality loss |
+| [airoboros-l2-7b-2.2.Q3_K_L.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b-2.2.Q3_K_L.gguf) | Q3_K_L | 3 | 3.60 GB| 6.10 GB | small, substantial quality loss |
+| [airoboros-l2-7b-2.2.Q4_0.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b-2.2.Q4_0.gguf) | Q4_0 | 4 | 3.83 GB| 6.33 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [airoboros-l2-7b-2.2.Q4_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b-2.2.Q4_K_S.gguf) | Q4_K_S | 4 | 3.86 GB| 6.36 GB | small, greater quality loss |
+| [airoboros-l2-7b-2.2.Q4_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b-2.2.Q4_K_M.gguf) | Q4_K_M | 4 | 4.08 GB| 6.58 GB | medium, balanced quality - recommended |
+| [airoboros-l2-7b-2.2.Q5_0.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b-2.2.Q5_0.gguf) | Q5_0 | 5 | 4.65 GB| 7.15 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [airoboros-l2-7b-2.2.Q5_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b-2.2.Q5_K_S.gguf) | Q5_K_S | 5 | 4.65 GB| 7.15 GB | large, low quality loss - recommended |
+| [airoboros-l2-7b-2.2.Q5_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b-2.2.Q5_K_M.gguf) | Q5_K_M | 5 | 4.78 GB| 7.28 GB | large, very low quality loss - recommended |
+| [airoboros-l2-7b-2.2.Q6_K.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b-2.2.Q6_K.gguf) | Q6_K | 6 | 5.53 GB| 8.03 GB | very large, extremely low quality loss |
+| [airoboros-l2-7b-2.2.Q8_0.gguf](https://huggingface.co/TheBloke/Airoboros-L2-7B-2.2-GGUF/blob/main/airoboros-l2-7b-2.2.Q8_0.gguf) | Q8_0 | 8 | 7.16 GB| 9.66 GB | very large, extremely low quality loss - not recommended |
 
 **Note**: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
 
@@ -135,7 +135,7 @@ Refer to the Provided Files table below to see what files use which methods, and
 Make sure you are using `llama.cpp` from commit [d0cee0d36d5be95a0d9088b674dbb27354107221](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221) or later.
 
 ```shell
-./main -ngl 32 -m airoboros-l2-7b.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "A chat.\nUSER: {prompt}\nASSISTANT:"
+./main -ngl 32 -m airoboros-l2-7b-2.2.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "A chat.\nUSER: {prompt}\nASSISTANT:"
 ```
 
 Change `-ngl 32` to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.
@@ -175,7 +175,7 @@ CT_METAL=1 pip install ctransformers>=0.2.24 --no-binary ctransformers
 from ctransformers import AutoModelForCausalLM
 
 # Set gpu_layers to the number of layers to offload to GPU. Set to 0 if no GPU acceleration is available on your system.
-llm = AutoModelForCausalLM.from_pretrained("TheBloke/Airoboros-L2-7B-2.2-GGUF", model_file="airoboros-l2-7b.q4_K_M.gguf", model_type="llama", gpu_layers=50)
+llm = AutoModelForCausalLM.from_pretrained("TheBloke/Airoboros-L2-7B-2.2-GGUF", model_file="airoboros-l2-7b-2.2.q4_K_M.gguf", model_type="llama", gpu_layers=50)
 
 print(llm("AI is going to"))
 ```