Upload README.md

README.md

@@ -1,10 +1,10 @@
 ---
+base_model: https://huggingface.co/jondurbin/airoboros-l2-70b-2.2
 datasets:
 - jondurbin/airoboros-2.2
 inference: false
 license: llama2
 model_creator: Jon Durbin
-model_link: https://huggingface.co/jondurbin/airoboros-l2-70b-2.2
 model_name: Airoboros L2 70B 2.2
 model_type: llama
 quantized_by: TheBloke
@@ -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-l2-70b.Q2_K.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b.Q2_K.gguf) | Q2_K | 2 | 29.28 GB| 31.78 GB | smallest, significant quality loss - not recommended for most purposes |
-| [airoboros-l2-70b.Q3_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b.Q3_K_S.gguf) | Q3_K_S | 3 | 29.92 GB| 32.42 GB | very small, high quality loss |
-| [airoboros-l2-70b.Q3_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b.Q3_K_M.gguf) | Q3_K_M | 3 | 33.19 GB| 35.69 GB | very small, high quality loss |
-| [airoboros-l2-70b.Q3_K_L.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b.Q3_K_L.gguf) | Q3_K_L | 3 | 36.15 GB| 38.65 GB | small, substantial quality loss |
-| [airoboros-l2-70b.Q4_0.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b.Q4_0.gguf) | Q4_0 | 4 | 38.87 GB| 41.37 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
-| [airoboros-l2-70b.Q4_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b.Q4_K_S.gguf) | Q4_K_S | 4 | 39.07 GB| 41.57 GB | small, greater quality loss |
-| [airoboros-l2-70b.Q4_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b.Q4_K_M.gguf) | Q4_K_M | 4 | 41.42 GB| 43.92 GB | medium, balanced quality - recommended |
-| [airoboros-l2-70b.Q5_0.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b.Q5_0.gguf) | Q5_0 | 5 | 47.46 GB| 49.96 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
-| [airoboros-l2-70b.Q5_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b.Q5_K_S.gguf) | Q5_K_S | 5 | 47.46 GB| 49.96 GB | large, low quality loss - recommended |
-| [airoboros-l2-70b.Q5_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b.Q5_K_M.gguf) | Q5_K_M | 5 | 48.75 GB| 51.25 GB | large, very low quality loss - recommended |
-| airoboros-l2-70b.Q6_K.gguf | Q6_K | 6 | 56.59 GB| 59.09 GB | very large, extremely low quality loss |
-| airoboros-l2-70b.Q8_0.gguf | Q8_0 | 8 | 73.29 GB| 75.79 GB | very large, extremely low quality loss - not recommended |
+| [airoboros-l2-70b-2.2.Q2_K.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b-2.2.Q2_K.gguf) | Q2_K | 2 | 29.28 GB| 31.78 GB | smallest, significant quality loss - not recommended for most purposes |
+| [airoboros-l2-70b-2.2.Q3_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b-2.2.Q3_K_S.gguf) | Q3_K_S | 3 | 29.92 GB| 32.42 GB | very small, high quality loss |
+| [airoboros-l2-70b-2.2.Q3_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b-2.2.Q3_K_M.gguf) | Q3_K_M | 3 | 33.19 GB| 35.69 GB | very small, high quality loss |
+| [airoboros-l2-70b-2.2.Q3_K_L.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b-2.2.Q3_K_L.gguf) | Q3_K_L | 3 | 36.15 GB| 38.65 GB | small, substantial quality loss |
+| [airoboros-l2-70b-2.2.Q4_0.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b-2.2.Q4_0.gguf) | Q4_0 | 4 | 38.87 GB| 41.37 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [airoboros-l2-70b-2.2.Q4_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b-2.2.Q4_K_S.gguf) | Q4_K_S | 4 | 39.07 GB| 41.57 GB | small, greater quality loss |
+| [airoboros-l2-70b-2.2.Q4_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b-2.2.Q4_K_M.gguf) | Q4_K_M | 4 | 41.42 GB| 43.92 GB | medium, balanced quality - recommended |
+| [airoboros-l2-70b-2.2.Q5_0.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b-2.2.Q5_0.gguf) | Q5_0 | 5 | 47.46 GB| 49.96 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [airoboros-l2-70b-2.2.Q5_K_S.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b-2.2.Q5_K_S.gguf) | Q5_K_S | 5 | 47.46 GB| 49.96 GB | large, low quality loss - recommended |
+| [airoboros-l2-70b-2.2.Q5_K_M.gguf](https://huggingface.co/TheBloke/Airoboros-L2-70b-2.2-GGUF/blob/main/airoboros-l2-70b-2.2.Q5_K_M.gguf) | Q5_K_M | 5 | 48.75 GB| 51.25 GB | large, very low quality loss - recommended |
+| airoboros-l2-70b-2.2.Q6_K.gguf | Q6_K | 6 | 56.59 GB| 59.09 GB | very large, extremely low quality loss |
+| airoboros-l2-70b-2.2.Q8_0.gguf | Q8_0 | 8 | 73.29 GB| 75.79 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.
 
@@ -134,28 +134,28 @@ Refer to the Provided Files table below to see what files use which methods, and
    
 ### q6_K 
 Please download:
-* `airoboros-l2-70b.Q6_K.gguf-split-a`
-* `airoboros-l2-70b.Q6_K.gguf-split-b`
+* `airoboros-l2-70b-2.2.Q6_K.gguf-split-a`
+* `airoboros-l2-70b-2.2.Q6_K.gguf-split-b`
 
 ### q8_0
 Please download:
-* `airoboros-l2-70b.Q8_0.gguf-split-a`
-* `airoboros-l2-70b.Q8_0.gguf-split-b`
+* `airoboros-l2-70b-2.2.Q8_0.gguf-split-a`
+* `airoboros-l2-70b-2.2.Q8_0.gguf-split-b`
 
 To join the files, do the following:
 
 Linux and macOS:
 ```
-cat airoboros-l2-70b.Q6_K.gguf-split-* > airoboros-l2-70b.Q6_K.gguf && rm airoboros-l2-70b.Q6_K.gguf-split-*
-cat airoboros-l2-70b.Q8_0.gguf-split-* > airoboros-l2-70b.Q8_0.gguf && rm airoboros-l2-70b.Q8_0.gguf-split-*
+cat airoboros-l2-70b-2.2.Q6_K.gguf-split-* > airoboros-l2-70b-2.2.Q6_K.gguf && rm airoboros-l2-70b-2.2.Q6_K.gguf-split-*
+cat airoboros-l2-70b-2.2.Q8_0.gguf-split-* > airoboros-l2-70b-2.2.Q8_0.gguf && rm airoboros-l2-70b-2.2.Q8_0.gguf-split-*
 ```
 Windows command line:
 ```
-COPY /B airoboros-l2-70b.Q6_K.gguf-split-a + airoboros-l2-70b.Q6_K.gguf-split-b airoboros-l2-70b.Q6_K.gguf
-del airoboros-l2-70b.Q6_K.gguf-split-a airoboros-l2-70b.Q6_K.gguf-split-b
+COPY /B airoboros-l2-70b-2.2.Q6_K.gguf-split-a + airoboros-l2-70b-2.2.Q6_K.gguf-split-b airoboros-l2-70b-2.2.Q6_K.gguf
+del airoboros-l2-70b-2.2.Q6_K.gguf-split-a airoboros-l2-70b-2.2.Q6_K.gguf-split-b
 
-COPY /B airoboros-l2-70b.Q8_0.gguf-split-a + airoboros-l2-70b.Q8_0.gguf-split-b airoboros-l2-70b.Q8_0.gguf
-del airoboros-l2-70b.Q8_0.gguf-split-a airoboros-l2-70b.Q8_0.gguf-split-b
+COPY /B airoboros-l2-70b-2.2.Q8_0.gguf-split-a + airoboros-l2-70b-2.2.Q8_0.gguf-split-b airoboros-l2-70b-2.2.Q8_0.gguf
+del airoboros-l2-70b-2.2.Q8_0.gguf-split-a airoboros-l2-70b-2.2.Q8_0.gguf-split-b
 ```
 
 </details>
@@ -167,7 +167,7 @@ del airoboros-l2-70b.Q8_0.gguf-split-a airoboros-l2-70b.Q8_0.gguf-split-b
 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-l2-70b.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-l2-70b-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.
@@ -207,7 +207,7 @@ 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-L2-70b-2.2-GGUF", model_file="airoboros-l2-70b.q4_K_M.gguf", model_type="llama", gpu_layers=50)
+llm = AutoModelForCausalLM.from_pretrained("TheBloke/Airoboros-L2-70b-2.2-GGUF", model_file="airoboros-l2-70b-2.2.q4_K_M.gguf", model_type="llama", gpu_layers=50)
 
 print(llm("AI is going to"))
 ```