Initial GGML model commit
Browse files
README.md
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---
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inference: false
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license: other
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---
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<!-- header start -->
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<div style="width: 100%;">
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<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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</div>
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<div style="display: flex; justify-content: space-between; width: 100%;">
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<div style="display: flex; flex-direction: column; align-items: flex-start;">
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<p><a href="https://discord.gg/Jq4vkcDakD">Chat & support: my new Discord server</a></p>
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</div>
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<div style="display: flex; flex-direction: column; align-items: flex-end;">
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<p><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
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</div>
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</div>
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<!-- header end -->
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# Bigcode's StarcoderPlus GGML
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These files are GGML format model files for [Bigcode's StarcoderPlus](https://huggingface.co/bigcode/starcoderplus).
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GGML files are for CPU + GPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp) and libraries and UIs which support this format, such as:
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* [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
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* [KoboldCpp](https://github.com/LostRuins/koboldcpp)
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* [ParisNeo/GPT4All-UI](https://github.com/ParisNeo/gpt4all-ui)
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* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)
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* [ctransformers](https://github.com/marella/ctransformers)
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## Repositories available
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* [4-bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/starcoderplus-GPTQ)
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* [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference](https://huggingface.co/TheBloke/starcoderplus-GGML)
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* [Unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/bigcode/starcoderplus)
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<!-- compatibility_ggml start -->
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## Compatibility
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### Original llama.cpp quant methods: `q4_0, q4_1, q5_0, q5_1, q8_0`
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I have quantized these 'original' quantisation methods using an older version of llama.cpp so that they remain compatible with llama.cpp as of May 19th, commit `2d5db48`.
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They should be compatible with all current UIs and libraries that use llama.cpp, such as those listed at the top of this README.
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### New k-quant methods: `q2_K, q3_K_S, q3_K_M, q3_K_L, q4_K_S, q4_K_M, q5_K_S, q6_K`
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These new quantisation methods are only compatible with llama.cpp as of June 6th, commit `2d43387`.
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They will NOT be compatible with koboldcpp, text-generation-ui, and other UIs and libraries yet. Support is expected to come over the next few days.
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## Explanation of the new k-quant methods
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The new methods available are:
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* 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)
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* 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.
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* 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.
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* GGML_TYPE_Q5_K - "type-1" 5-bit quantization. Same super-block structure as GGML_TYPE_Q4_K resulting in 5.5 bpw
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* 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
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* GGML_TYPE_Q8_K - "type-0" 8-bit quantization. Only used for quantizing intermediate results. The difference to the existing Q8_0 is that the block size is 256. All 2-6 bit dot products are implemented for this quantization type.
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Refer to the Provided Files table below to see what files use which methods, and how.
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<!-- compatibility_ggml end -->
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## Provided files
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| Name | Quant method | Bits | Size | Max RAM required | Use case |
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| ---- | ---- | ---- | ---- | ---- | ----- |
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| starcoderplus.ggmlv3.q4_0.bin | q4_0 | 4 | 10.75 GB | 13.25 GB | Original llama.cpp quant method, 4-bit. |
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| starcoderplus.ggmlv3.q4_1.bin | q4_1 | 4 | 11.92 GB | 14.42 GB | Original llama.cpp quant method, 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
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| starcoderplus.ggmlv3.q5_0.bin | q5_0 | 5 | 13.09 GB | 15.59 GB | Original llama.cpp quant method, 5-bit. Higher accuracy, higher resource usage and slower inference. |
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| starcoderplus.ggmlv3.q5_1.bin | q5_1 | 5 | 14.26 GB | 16.76 GB | Original llama.cpp quant method, 5-bit. Even higher accuracy, resource usage and slower inference. |
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| starcoderplus.ggmlv3.q8_0.bin | q8_0 | 8 | 20.11 GB | 22.61 GB | Original llama.cpp quant method, 8-bit. Almost indistinguishable from float16. High resource use and slow. Not recommended for most users. |
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**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.
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## How to run in `llama.cpp`
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I use the following command line; adjust for your tastes and needs:
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```
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./main -t 10 -ngl 32 -m starcoder-plus.ggmlv3.q5_0.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "### Instruction: Write a story about llamas\n### Response:"
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```
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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`.
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Change `-ngl 32` to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.
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If you want to have a chat-style conversation, replace the `-p <PROMPT>` argument with `-i -ins`
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## How to run in `text-generation-webui`
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Further instructions here: [text-generation-webui/docs/llama.cpp-models.md](https://github.com/oobabooga/text-generation-webui/blob/main/docs/llama.cpp-models.md).
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<!-- footer start -->
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## Discord
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For further support, and discussions on these models and AI in general, join us at:
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[TheBloke AI's Discord server](https://discord.gg/Jq4vkcDakD)
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## Thanks, and how to contribute.
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Thanks to the [chirper.ai](https://chirper.ai) team!
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I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.
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If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.
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Donaters will get priority support on any and all AI/LLM/model questions and requests, access to a private Discord room, plus other benefits.
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* Patreon: https://patreon.com/TheBlokeAI
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* Ko-Fi: https://ko-fi.com/TheBlokeAI
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**Special thanks to**: Luke from CarbonQuill, Aemon Algiz, Dmitriy Samsonov.
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**Patreon special mentions**: Ajan Kanaga, Kalila, Derek Yates, Sean Connelly, Luke, Nathan LeClaire, Trenton Dambrowitz, Mano Prime, David Flickinger, vamX, Nikolai Manek, senxiiz, Khalefa Al-Ahmad, Illia Dulskyi, trip7s trip, Jonathan Leane, Talal Aujan, Artur Olbinski, Cory Kujawski, Joseph William Delisle, Pyrater, Oscar Rangel, Lone Striker, Luke Pendergrass, Eugene Pentland, Johann-Peter Hartmann.
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Thank you to all my generous patrons and donaters!
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<!-- footer end -->
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# Original model card: Bigcode's StarcoderPlus
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No original model card was provided.
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