New GGMLv3 format for breaking llama.cpp change May 19th commit 2d5db48

README.md

@@ -15,20 +15,21 @@ This repo contains GGML files for for CPU inference using [llama.cpp](https://gi
 * [4bit and 5bit GGML models for CPU inference in llama.cpp](https://huggingface.co/TheBloke/dromedary-65B-lora-GGML)
 * [float16 unquantised model for GPU](https://huggingface.co/TheBloke/dromedary-65B-lora-HF)
 
-## REQUIRES LATEST LLAMA.CPP (May 12th 2023 - commit b9fd7ee)!
+## THE FILES IN MAIN BRANCH REQUIRES LATEST LLAMA.CPP (May 19th 2023 - commit 2d5db48)!
 
-llama.cpp recently made a breaking change to its quantisation methods.
+llama.cpp recently made another breaking change to its quantisation methods - https://github.com/ggerganov/llama.cpp/pull/1508
 
-I have re-quantised the GGML files in this repo. Therefore you will require llama.cpp compiled on May 12th or later (commit `b9fd7ee` or later) to use them.
+I have quantised the GGML files in this repo with the latest version. Therefore you will require llama.cpp compiled on May 19th or later (commit `2d5db48` or later) to use them.
 
-The previous files, which will still work in older versions of llama.cpp, can be found in branch `previous_llama`.
+For files compatible with the previous version of llama.cpp, please see branch `previous_llama_ggmlv2`.
 
 ## Provided files
 | Name | Quant method | Bits | Size | RAM required | Use case |
 | ---- | ---- | ---- | ---- | ---- | ----- |
-`dromedary-lora-65B.ggml.q4_0.bin` | q4_0 | 4bit | 40.8GB | 43GB | 4-bit. |
-`dromedary-lora-65B.ggml.q5_0.bin` | q5_0 | 5bit | 44.9GB | 47GB | 5-bit. Higher accuracy, higher resource usage and slower inference.  |
-`dromedary-lora-65B.ggml.q5_1.bin` | q5_1 | 5bit | 49GB | 51GB | 5-bit. Even higher accuracy, higher resource usage and slower inference. |
+`dromedary-lora-65B.ggmlv3.q4_0.bin` | q4_0 | 4bit | 40.8GB | 43GB | 4-bit. |
+`dromedary-lora-65B.ggmlv3.q4_1.bin` | q4_1 | 4bit | 44.9GB | 47GB | 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
+`dromedary-lora-65B.ggmlv3.q5_0.bin` | q5_0 | 5bit | 44.9GB | 47GB | 5-bit. Higher accuracy, higher resource usage and slower inference.  |
+`dromedary-lora-65B.ggmlv3.q5_1.bin` | q5_1 | 5bit | 49GB | 51GB | 5-bit. Even higher accuracy, higher resource usage and slower inference. |
 
 
 # Original Dromedary Model Card
@@ -80,4 +81,4 @@ We use the following configuration for the LoRA weights:
 Fewer than 300 lines of human annotations (including < 200 seed prompts, 16 generic principles, and 5 exemplars for in-context learning),
 
 ## Evaluation dataset
-We evaluate Dromedary on TruthfulQA and HHH Eval, as well as Vicuna benchmark questions.
+We evaluate Dromedary on TruthfulQA and HHH Eval, as well as Vicuna benchmark questions.