Initial GGUF model commit

README.md

@@ -8,7 +8,7 @@ language:
 license: llama2
 model_creator: OpenAssistant
 model_link: https://huggingface.co/OpenAssistant/codellama-13b-oasst-sft-v10
-model_name: CodeLlama 13B OASST SFT v10
+model_name: CodeLlama 13B SFT v10
 model_type: llama
 quantized_by: TheBloke
 ---
@@ -30,13 +30,13 @@ quantized_by: TheBloke
 <hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
 <!-- header end -->
 
-# CodeLlama 13B OASST SFT v10 - GGUF
+# CodeLlama 13B SFT v10 - GGUF
 - Model creator: [OpenAssistant](https://huggingface.co/OpenAssistant)
-- Original model: [CodeLlama 13B OASST SFT v10](https://huggingface.co/OpenAssistant/codellama-13b-oasst-sft-v10)
+- Original model: [CodeLlama 13B SFT v10](https://huggingface.co/OpenAssistant/codellama-13b-oasst-sft-v10)
 
 ## Description
 
-This repo contains GGUF format model files for [OpenAssistant's CodeLlama 13B OASST SFT v10](https://huggingface.co/OpenAssistant/codellama-13b-oasst-sft-v10).
+This repo contains GGUF format model files for [OpenAssistant's CodeLlama 13B SFT v10](https://huggingface.co/OpenAssistant/codellama-13b-oasst-sft-v10).
 
 <!-- README_GGUF.md-about-gguf start -->
 ### About GGUF
@@ -61,9 +61,9 @@ The clients and libraries below are expecting to add GGUF support shortly:
 <!-- repositories-available start -->
 ## Repositories available
 
-* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GPTQ)
-* [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GGUF)
-* [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference (deprecated)](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GGML)
+* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/CodeLlama-13B-OASST-SFT-v10-GPTQ)
+* [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/CodeLlama-13B-OASST-SFT-v10-GGUF)
+* [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference (deprecated)](https://huggingface.co/TheBloke/CodeLlama-13B-OASST-SFT-v10-GGML)
 * [OpenAssistant's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/OpenAssistant/codellama-13b-oasst-sft-v10)
 <!-- repositories-available end -->
 
@@ -109,16 +109,18 @@ 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 |
 | ---- | ---- | ---- | ---- | ---- | ----- |
-| [codellama-13b-oasst-sft-v10.Q2_K.gguf](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GGUF/blob/main/codellama-13b-oasst-sft-v10.Q2_K.gguf) | Q2_K | 2 | 5.43 GB| 7.93 GB | smallest, significant quality loss - not recommended for most purposes |
-| [codellama-13b-oasst-sft-v10.Q3_K_S.gguf](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GGUF/blob/main/codellama-13b-oasst-sft-v10.Q3_K_S.gguf) | Q3_K_S | 3 | 5.66 GB| 8.16 GB | very small, high quality loss |
-| [codellama-13b-oasst-sft-v10.Q3_K_M.gguf](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GGUF/blob/main/codellama-13b-oasst-sft-v10.Q3_K_M.gguf) | Q3_K_M | 3 | 6.34 GB| 8.84 GB | very small, high quality loss |
-| [codellama-13b-oasst-sft-v10.Q3_K_L.gguf](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GGUF/blob/main/codellama-13b-oasst-sft-v10.Q3_K_L.gguf) | Q3_K_L | 3 | 6.93 GB| 9.43 GB | small, substantial quality loss |
-| [codellama-13b-oasst-sft-v10.Q4_K_S.gguf](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GGUF/blob/main/codellama-13b-oasst-sft-v10.Q4_K_S.gguf) | Q4_K_S | 4 | 7.41 GB| 9.91 GB | small, greater quality loss |
-| [codellama-13b-oasst-sft-v10.Q4_K_M.gguf](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GGUF/blob/main/codellama-13b-oasst-sft-v10.Q4_K_M.gguf) | Q4_K_M | 4 | 7.87 GB| 10.37 GB | medium, balanced quality - recommended |
-| [codellama-13b-oasst-sft-v10.Q5_K_S.gguf](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GGUF/blob/main/codellama-13b-oasst-sft-v10.Q5_K_S.gguf) | Q5_K_S | 5 | 8.97 GB| 11.47 GB | large, low quality loss - recommended |
-| [codellama-13b-oasst-sft-v10.Q5_K_M.gguf](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GGUF/blob/main/codellama-13b-oasst-sft-v10.Q5_K_M.gguf) | Q5_K_M | 5 | 9.23 GB| 11.73 GB | large, very low quality loss - recommended |
-| [codellama-13b-oasst-sft-v10.Q6_K.gguf](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GGUF/blob/main/codellama-13b-oasst-sft-v10.Q6_K.gguf) | Q6_K | 6 | 10.68 GB| 13.18 GB | very large, extremely low quality loss |
-| [codellama-13b-oasst-sft-v10.Q8_0.gguf](https://huggingface.co/TheBloke/CodeLlama-13B-oasst-sft-v10-GGUF/blob/main/codellama-13b-oasst-sft-v10.Q8_0.gguf) | Q8_0 | 8 | 13.83 GB| 16.33 GB | very large, extremely low quality loss - not recommended |
+| codellama-13b-oasst-sft-v10.Q2_K.gguf | Q2_K | 2 | 5.43 GB| 7.93 GB | smallest, significant quality loss - not recommended for most purposes |
+| codellama-13b-oasst-sft-v10.Q3_K_S.gguf | Q3_K_S | 3 | 5.66 GB| 8.16 GB | very small, high quality loss |
+| codellama-13b-oasst-sft-v10.Q3_K_M.gguf | Q3_K_M | 3 | 6.34 GB| 8.84 GB | very small, high quality loss |
+| codellama-13b-oasst-sft-v10.Q3_K_L.gguf | Q3_K_L | 3 | 6.93 GB| 9.43 GB | small, substantial quality loss |
+| codellama-13b-oasst-sft-v10.Q4_0.gguf | Q4_0 | 4 | 7.37 GB| 9.87 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| codellama-13b-oasst-sft-v10.Q4_K_S.gguf | Q4_K_S | 4 | 7.41 GB| 9.91 GB | small, greater quality loss |
+| codellama-13b-oasst-sft-v10.Q4_K_M.gguf | Q4_K_M | 4 | 7.87 GB| 10.37 GB | medium, balanced quality - recommended |
+| codellama-13b-oasst-sft-v10.Q5_0.gguf | Q5_0 | 5 | 8.97 GB| 11.47 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| codellama-13b-oasst-sft-v10.Q5_K_S.gguf | Q5_K_S | 5 | 8.97 GB| 11.47 GB | large, low quality loss - recommended |
+| codellama-13b-oasst-sft-v10.Q5_K_M.gguf | Q5_K_M | 5 | 9.23 GB| 11.73 GB | large, very low quality loss - recommended |
+| codellama-13b-oasst-sft-v10.Q6_K.gguf | Q6_K | 6 | 10.68 GB| 13.18 GB | very large, extremely low quality loss |
+| codellama-13b-oasst-sft-v10.Q8_0.gguf | Q8_0 | 8 | 13.83 GB| 16.33 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.
 <!-- README_GGUF.md-provided-files end -->
@@ -131,7 +133,7 @@ Make sure you are using `llama.cpp` from commit [6381d4e110bd0ec02843a60bbeb8b6f
 For compatibility with older versions of llama.cpp, or for use with third-party clients and libaries, please use GGML files instead.
 
 ```
-./main -t 10 -ngl 32 -m codellama-13b-oasst-sft-v10.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "### Instruction: Write a story about llamas\n### Response:"
+./main -t 10 -ngl 32 -m codellama-13b-oasst-sft-v10.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "<|im_start|>system\nYou are a story writing assistant.<|im_end|>\n<|im_start|>user\nWrite a story about llamas<|im_end|>\n<|im_start|>assistant"
 ```
 Change `-t 10` to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use `-t 8`.
 
@@ -181,7 +183,7 @@ And thank you again to a16z for their generous grant.
 <!-- footer end -->
 
 <!-- original-model-card start -->
-# Original model card: OpenAssistant's CodeLlama 13B OASST SFT v10
+# Original model card: OpenAssistant's CodeLlama 13B SFT v10
 
 # Open-Assistant CodeLlama 13B SFT v10