Manoj Preveen's MPT 30B Dolphin v2 GGML
These files are MPT GGML format model files for Manoj Preveen's MPT 30B Dolphin v2.
Please note that these GGMLs are not compatible with llama.cpp, or currently with text-generation-webui. Please see below for a list of tools that work with this GGML model.
Repositories available
- 2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference
- Unquantised fp16 model in pytorch format, for GPU inference and for further conversions
Prompt template: custom
<system>: You are a helpful assistant
<human>: {prompt}
<bot>:
Compatibilty
These files are not compatible with llama.cpp or text-generation-webui.
They can be used with:
- KoboldCpp, a powerful inference engine based on llama.cpp with full GPU acceleration and good UI.
- LM Studio, a fully featured local GUI for GGML inference on Windows and macOS.
- LoLLMs-WebUI a web UI which supports nearly every backend out there. Use ctransformers backend for support for this model.
- ctransformers: for use in Python code, including LangChain support.
- rustformers' llm
- The example
mptbinary provided with ggml
As other options become available I will endeavour to update them here (do let me know in the Community tab if I've missed something!)
Tutorial for using LoLLMs-WebUI:
Provided files
| Name | Quant method | Bits | Size | Max RAM required | Use case |
|---|---|---|---|---|---|
| mpt-30b-dolphin-v2.ggmlv1.q4_0.bin | q4_0 | 4 | 16.85 GB | 19.35 GB | 4-bit. |
| mpt-30b-dolphin-v2.ggmlv1.q4_1.bin | q4_1 | 4 | 18.73 GB | 21.23 GB | 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
| mpt-30b-dolphin-v2.ggmlv1.q5_0.bin | q5_0 | 5 | 20.60 GB | 23.10 GB | 5-bit. Higher accuracy, higher resource usage and slower inference. |
| mpt-30b-dolphin-v2.ggmlv1.q5_1.bin | q5_1 | 5 | 22.47 GB | 24.97 GB | 5-bit. Even higher accuracy, resource usage and slower inference. |
| mpt-30b-dolphin-v2.ggmlv1.q8_0.bin | q8_0 | 8 | 31.83 GB | 34.33 GB | 8-bit. Almost indistinguishable from float16. High resource use and slow. Not recommended for most users. |
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.
Discord
For further support, and discussions on these models and AI in general, join us at:
Thanks, and how to contribute.
Thanks to the chirper.ai team!
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.
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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Special thanks to: Luke from CarbonQuill, Aemon Algiz.
Patreon special mentions: RoA, Lone Striker, Gabriel Puliatti, Derek Yates, Randy H, Jonathan Leane, Eugene Pentland, Karl Bernard, Viktor Bowallius, senxiiz, Daniel P. Andersen, Pierre Kircher, Deep Realms, Cory Kujawski, Oscar Rangel, Fen Risland, Ajan Kanaga, LangChain4j, webtim, Nikolai Manek, Trenton Dambrowitz, Raven Klaugh, Kalila, Khalefa Al-Ahmad, Chris McCloskey, Luke @flexchar, Ai Maven, Dave, Asp the Wyvern, Sean Connelly, Imad Khwaja, Space Cruiser, Rainer Wilmers, subjectnull, Alps Aficionado, Willian Hasse, Fred von Graf, Artur Olbinski, Johann-Peter Hartmann, WelcomeToTheClub, Willem Michiel, Michael Levine, Iucharbius , Spiking Neurons AB, K, biorpg, John Villwock, Pyrater, Greatston Gnanesh, Mano Prime, Junyu Yang, Stephen Murray, John Detwiler, Luke Pendergrass, terasurfer , Pieter, zynix , Edmond Seymore, theTransient, Nathan LeClaire, vamX, Kevin Schuppel, Preetika Verma, ya boyyy, Alex , SuperWojo, Ghost , Joseph William Delisle, Matthew Berman, Talal Aujan, chris gileta, Illia Dulskyi.
Thank you to all my generous patrons and donaters!
Original model card: Manoj Preveen's MPT 30B Dolphin v2
Base Model : mosaicml/mpt-30b
Tool : MosaicML's llm-foundry (https://github.com/mosaicml/llm-foundry)
Dataset : Entire flan3m-GPT3.5 dataset.
Config yaml with Model Params : https://huggingface.co/manojpreveen/mpt-30b-orca-v2/blob/main/mpt-30b_orca.yaml
Prompt Format :
<system>: [system prompt]
<human>: [question]
<bot>: