--- pipeline_tag: text-generation tags: - not-for-all-audiences - GGUF - KoboldAI/LLaMA2-13B-Psyfighter2 - KoboldAI/LLaMA2-13B-Erebus-v3 model_type: llama2 model_name: 13B-Psyfighter2-Erebus3-DareTies quantized_by: DaveGergern base_model: DaveGergern/13B-Psyfighter2-Erebus3-DareTies license: llama2 --- ## Description This repo contains GGUF format model files for [13B-Psyfighter2-Erebus3-DareTies](https://huggingface.co/DaveGergern/13B-Psyfighter2-Erebus3-DareTies). ### About GGUF GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Here is an incomplete list of clients and libraries that are known to support GGUF: * [llama.cpp](https://github.com/ggerganov/llama.cpp). The source project for GGUF. Offers a CLI and a server option. * [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration. * [KoboldCpp](https://github.com/LostRuins/koboldcpp), a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling. * [GPT4All](https://gpt4all.io/index.html), a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel. * [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration. Linux available, in beta as of 27/11/2023. * [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), a great web UI with many interesting and unique features, including a full model library for easy model selection. * [Faraday.dev](https://faraday.dev/), an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration. * [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), a Python library with GPU accel, LangChain support, and OpenAI-compatible API server. * [candle](https://github.com/huggingface/candle), a Rust ML framework with a focus on performance, including GPU support, and ease of use. * [ctransformers](https://github.com/marella/ctransformers), a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server. Note, as of time of writing (November 27th 2023), ctransformers has not been updated in a long time and does not support many recent models. ## Prompt template: Alpaca-Tiefighter ``` ### Instruction: {prompt} ### Response: ``` ## Compatibility These quantised GGUFv2 files are compatible with llama.cpp from August 27th onwards, as of commit [d0cee0d](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221) They are also compatible with many third party UIs and libraries - please see the list at the top of this README. ## Explanation of quantisation methods
Click to see details The new methods available are: * GGML_TYPE_Q2_K - "type-1" 2-bit quantization in super-blocks containing 16 blocks, each block having 16 weight. Block scales and mins are quantized with 4 bits. This ends up effectively using 2.5625 bits per weight (bpw) * GGML_TYPE_Q3_K - "type-0" 3-bit quantization in super-blocks containing 16 blocks, each block having 16 weights. Scales are quantized with 6 bits. This end up using 3.4375 bpw. * GGML_TYPE_Q4_K - "type-1" 4-bit quantization in super-blocks containing 8 blocks, each block having 32 weights. Scales and mins are quantized with 6 bits. This ends up using 4.5 bpw. * GGML_TYPE_Q5_K - "type-1" 5-bit quantization. Same super-block structure as GGML_TYPE_Q4_K resulting in 5.5 bpw * GGML_TYPE_Q6_K - "type-0" 6-bit quantization. Super-blocks with 16 blocks, each block having 16 weights. Scales are quantized with 8 bits. This ends up using 6.5625 bpw Refer to the Provided Files table below to see what files use which methods, and how.
## Provided files | File | Quantize | Size | |------|----------|------| | [LLaMA2-13B-Psyfighter2-Erebus3-DareTies-fp16.gguf](LLaMA2-13B-Psyfighter2-Erebus3-DareTies-fp16.gguf) | fp16 | 26GiB | | [LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q2_K.gguf](LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q2_K.gguf) | Q2_K | 1.8GiB | | [LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q3_K_L.gguf](LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q3_K_L.gguf) | Q3_K_L | 6.9GiB | | [LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q3_K_M.gguf](LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q3_K_M.gguf) | Q3_K_M | 6.3GiB | | [LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q3_K_S.gguf](LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q3_K_S.gguf) | Q3_K_S | 5.6GiB | | [LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q4_K_M.gguf](LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q4_K_M.gguf) | Q4_K_M | 7.8GiB | | [LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q4_K_S.gguf](LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q4_K_S.gguf) | Q4_K_S | 7.4GiB | | [LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q5_K_M.gguf](LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q5_K_M.gguf) | Q5_K_M | 9.2GiB | | [LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q5_K_S.gguf](LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q5_K_S.gguf) | Q5_K_S | 8.9GiB | | [LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q6_K.gguf](LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q6_K.gguf) | Q6_K | 10GiB | | [LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q8_0.gguf](LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q8_0.gguf) | Q8_0 | 13GiB |