Information
OpenAssistant-Llama-30B-4-bit working with GPTQ versions used in Oobabooga's Text Generation Webui and KoboldAI.This was made using Open Assistant's native fine-tune of Llama 30b on their dataset.
What's included
GPTQ: 2 quantized versions. One quantized --true-sequential and act-order optimizations, and the other was quantized using --true-sequential --groupsize 128 optimizations
GGML: 3 quantized versions. One quantized using q4_1, another one was quantized using q5_0, and the last one was quantized using q5_1.
Update 05.27.2023
Updated the ggml quantizations to be compatible with the latest version of llamacpp (again).
Update 04.29.2023
Updated to the latest fine-tune by Open Assistant oasst-sft-7-llama-30b-xor.
GPU/GPTQ Usage
To use with your GPU using GPTQ pick one of the .safetensors along with all of the .jsons and .model files.
Oobabooga: If you require further instruction, see here and here
KoboldAI: If you require further instruction, see here
CPU/GGML Usage
To use your CPU using GGML(Llamacpp) you only need the single .bin ggml file.
Oobabooga: If you require further instruction, see here
KoboldAI: If you require further instruction, see here
Benchmarks
--true-sequential --act-order
Wikitext2: 4.964076519012451
Ptb-New: 9.641128540039062
C4-New: 7.203001022338867
Note: This version does not use --groupsize 128, therefore evaluations are minimally higher. However, this version allows fitting the whole model at full context using only 24GB VRAM.
--true-sequential --groupsize 128
Wikitext2: 4.641914367675781
Ptb-New: 9.117929458618164
C4-New: 6.867942810058594
Note: This version uses --groupsize 128, resulting in better evaluations. However, it consumes more VRAM.
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