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TheBloke's LLM work is generously supported by a grant from andreessen horowitz (a16z)
# GPT4All-13B-snoozy-GPTQ
This repo contains 4bit GPTQ format quantised models of Nomic.AI's GPT4all-13B-snoozy.
It is the result of quantising to 4bit using GPTQ-for-LLaMa.
Repositories available
- 4bit GPTQ models for GPU inference.
- 4bit and 5bit GGML models for GPU inference.
- Nomic.AI's original model in float32 HF for GPU inference.
How to easily download and use this model in text-generation-webui
Open the text-generation-webui UI as normal.
- Click the Model tab.
- Under Download custom model or LoRA, enter
TheBloke/GPT4All-13B-snoozy-GPTQ
. - Click Download.
- Wait until it says it's finished downloading.
- Click the Refresh icon next to Model in the top left.
- In the Model drop-down: choose the model you just downloaded,
GPT4All-13B-snoozy-GPTQ
. - If you see an error in the bottom right, ignore it - it's temporary.
- Fill out the
GPTQ parameters
on the right:Bits = 4
,Groupsize = 128
,model_type = Llama
- Click Save settings for this model in the top right.
- Click Reload the Model in the top right.
- Once it says it's loaded, click the Text Generation tab and enter a prompt!
Provided files
Compatible file - GPT4ALL-13B-GPTQ-4bit-128g.compat.no-act-order.safetensors
In the main
branch - the default one - you will find GPT4ALL-13B-GPTQ-4bit-128g.compat.no-act-order.safetensors
This will work with all versions of GPTQ-for-LLaMa. It has maximum compatibility
It was created without the --act-order
parameter. It may have slightly lower inference quality compared to the other file, but is guaranteed to work on all versions of GPTQ-for-LLaMa and text-generation-webui.
GPT4ALL-13B-GPTQ-4bit-128g.compat.no-act-order.safetensors
- Works with all versions of GPTQ-for-LLaMa code, both Triton and CUDA branches
- Works with text-generation-webui one-click-installers
- Parameters: Groupsize = 128g. No act-order.
- Command used to create the GPTQ:
CUDA_VISIBLE_DEVICES=0 python3 llama.py GPT4All-13B-snoozy c4 --wbits 4 --true-sequential --groupsize 128 --save_safetensors GPT4ALL-13B-GPTQ-4bit-128g.compat.no-act-order.safetensors
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.
Donaters will get priority support on any and all AI/LLM/model questions and requests, access to a private Discord room, plus other benefits.
- Patreon: https://patreon.com/TheBlokeAI
- Ko-Fi: https://ko-fi.com/TheBlokeAI
Special thanks to: Aemon Algiz.
Patreon special mentions: Sam, theTransient, Jonathan Leane, Steven Wood, webtim, Johann-Peter Hartmann, Geoffrey Montalvo, Gabriel Tamborski, Willem Michiel, John Villwock, Derek Yates, Mesiah Bishop, Eugene Pentland, Pieter, Chadd, Stephen Murray, Daniel P. Andersen, terasurfer, Brandon Frisco, Thomas Belote, Sid, Nathan LeClaire, Magnesian, Alps Aficionado, Stanislav Ovsiannikov, Alex, Joseph William Delisle, Nikolai Manek, Michael Davis, Junyu Yang, K, J, Spencer Kim, Stefan Sabev, Olusegun Samson, transmissions 11, Michael Levine, Cory Kujawski, Rainer Wilmers, zynix, Kalila, Luke @flexchar, Ajan Kanaga, Mandus, vamX, Ai Maven, Mano Prime, Matthew Berman, subjectnull, Vitor Caleffi, Clay Pascal, biorpg, alfie_i, 阿明, Jeffrey Morgan, ya boyyy, Raymond Fosdick, knownsqashed, Olakabola, Leonard Tan, ReadyPlayerEmma, Enrico Ros, Dave, Talal Aujan, Illia Dulskyi, Sean Connelly, senxiiz, Artur Olbinski, Elle, Raven Klaugh, Fen Risland, Deep Realms, Imad Khwaja, Fred von Graf, Will Dee, usrbinkat, SuperWojo, Alexandros Triantafyllidis, Swaroop Kallakuri, Dan Guido, John Detwiler, Pedro Madruga, Iucharbius, Viktor Bowallius, Asp the Wyvern, Edmond Seymore, Trenton Dambrowitz, Space Cruiser, Spiking Neurons AB, Pyrater, LangChain4j, Tony Hughes, Kacper Wikieł, Rishabh Srivastava, David Ziegler, Luke Pendergrass, Andrey, Gabriel Puliatti, Lone Striker, Sebastain Graf, Pierre Kircher, Randy H, NimbleBox.ai, Vadim, danny, Deo Leter
Thank you to all my generous patrons and donaters!
And thank you again to a16z for their generous grant.
Original Model Card for GPT4All-13b-snoozy
An Apache-2 licensed chatbot trained over a massive curated corpus of assistant interactions including word problems, multi-turn dialogue, code, poems, songs, and stories.
Model Details
Model Description
This model has been finetuned from LLama 13B
- Developed by: Nomic AI
- Model Type: A finetuned LLama 13B model on assistant style interaction data
- Language(s) (NLP): English
- License: Apache-2
- Finetuned from model [optional]: LLama 13B
This model was trained on nomic-ai/gpt4all-j-prompt-generations
using revision=v1.3-groovy
Model Sources [optional]
- Repository: https://github.com/nomic-ai/gpt4all
- Base Model Repository: https://github.com/facebookresearch/llama
- Demo [optional]: https://gpt4all.io/
Results
Results on common sense reasoning benchmarks
Model BoolQ PIQA HellaSwag WinoGrande ARC-e ARC-c OBQA
----------------------- ---------- ---------- ----------- ------------ ---------- ---------- ----------
GPT4All-J 6B v1.0 73.4 74.8 63.4 64.7 54.9 36.0 40.2
GPT4All-J v1.1-breezy 74.0 75.1 63.2 63.6 55.4 34.9 38.4
GPT4All-J v1.2-jazzy 74.8 74.9 63.6 63.8 56.6 35.3 41.0
GPT4All-J v1.3-groovy 73.6 74.3 63.8 63.5 57.7 35.0 38.8
GPT4All-J Lora 6B 68.6 75.8 66.2 63.5 56.4 35.7 40.2
GPT4All LLaMa Lora 7B 73.1 77.6 72.1 67.8 51.1 40.4 40.2
GPT4All 13B snoozy *83.3* 79.2 75.0 *71.3* 60.9 44.2 43.4
Dolly 6B 68.8 77.3 67.6 63.9 62.9 38.7 41.2
Dolly 12B 56.7 75.4 71.0 62.2 *64.6* 38.5 40.4
Alpaca 7B 73.9 77.2 73.9 66.1 59.8 43.3 43.4
Alpaca Lora 7B 74.3 *79.3* 74.0 68.8 56.6 43.9 42.6
GPT-J 6B 65.4 76.2 66.2 64.1 62.2 36.6 38.2
LLama 7B 73.1 77.4 73.0 66.9 52.5 41.4 42.4
LLama 13B 68.5 79.1 *76.2* 70.1 60.0 *44.6* 42.2
Pythia 6.9B 63.5 76.3 64.0 61.1 61.3 35.2 37.2
Pythia 12B 67.7 76.6 67.3 63.8 63.9 34.8 38.0
Vicuña T5 81.5 64.6 46.3 61.8 49.3 33.3 39.4
Vicuña 13B 81.5 76.8 73.3 66.7 57.4 42.7 43.6
Stable Vicuña RLHF 82.3 78.6 74.1 70.9 61.0 43.5 *44.4*
StableLM Tuned 62.5 71.2 53.6 54.8 52.4 31.1 33.4
StableLM Base 60.1 67.4 41.2 50.1 44.9 27.0 32.0
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