Description
This repo contains GGUF format model files for 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. The source project for GGUF. Offers a CLI and a server option.
- text-generation-webui, the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
- KoboldCpp, a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
- GPT4All, a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
- LM Studio, 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, a great web UI with many interesting and unique features, including a full model library for easy model selection.
- 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, a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
- candle, a Rust ML framework with a focus on performance, including GPU support, and ease of use.
- 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
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 | fp16 | 26GiB |
LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q2_K.gguf | Q2_K | 1.8GiB |
LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q3_K_L.gguf | Q3_K_L | 6.9GiB |
LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q3_K_M.gguf | Q3_K_M | 6.3GiB |
LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q3_K_S.gguf | Q3_K_S | 5.6GiB |
LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q4_K_M.gguf | Q4_K_M | 7.8GiB |
LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q4_K_S.gguf | Q4_K_S | 7.4GiB |
LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q5_K_M.gguf | Q5_K_M | 9.2GiB |
LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q5_K_S.gguf | Q5_K_S | 8.9GiB |
LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q6_K.gguf | Q6_K | 10GiB |
LLaMA2-13B-Psyfighter2-Erebus3-DareTies-Q8_0.gguf | Q8_0 | 13GiB |
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Model tree for DaveGergern/LLaMA2-13B-Psyfighter2-Erebus3-DareTies-GGUF
Base model
DaveGergern/13B-Psyfighter2-Erebus3-DareTies