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--- |
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license: gpl |
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datasets: |
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- nomic-ai/gpt4all-j-prompt-generations |
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language: |
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- en |
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inference: false |
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--- |
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# GPT4All-13B-snoozy-GGML |
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These files are GGML format model files of [Nomic.AI's GPT4all-13B-snoozy](https://huggingface.co/nomic-ai/gpt4all-13b-snoozy). |
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GGML files are for CPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp). |
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## Repositories available |
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* [4bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/GPT4ALL-13B-snoozy-GPTQ). |
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* [4bit and 5bit GGML models for GPU inference](https://huggingface.co/TheBloke/GPT4ALL-13B-snoozy-GGML). |
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* [Nomic.AI's original model in float32 HF for GPU inference](https://huggingface.co/nomic-ai/gpt4all-13b-snoozy). |
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## Provided files |
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| Name | Quant method | Bits | Size | RAM required | Use case | |
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| ---- | ---- | ---- | ---- | ---- | ----- | |
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`GPT4All-13B-snoozy.q4_0.bin` | q4_0 | 4bit | 8.14GB | 10GB | Maximum compatibility | |
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`GPT4All-13B-snoozy.q4_2.bin` | q4_2 | 4bit | 8.14GB | 10GB | Best compromise between resources, speed and quality | |
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`GPT4All-13B-snoozy.q5_0.bin` | q5_0 | 5bit | 8.95GB | 11GB | Brand new 5bit method. Potentially higher quality than 4bit, at cost of slightly higher resources. | |
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`GPT4All-13B-snoozy.q5_1.bin` | q5_1 | 5bit | 9.76GB | 12GB | Brand new 5bit method. Slightly higher resource usage than q5_0.| |
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* The q4_0 file provides lower quality, but maximal compatibility. It will work with past and future versions of llama.cpp |
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* The q4_2 file offers the best combination of performance and quality. This format is still subject to change and there may be compatibility issues, see below. |
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* The q5_0 file is using brand new 5bit method released 26th April. This is the 5bit equivalent of q4_0. |
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* The q5_1 file is using brand new 5bit method released 26th April. This is the 5bit equivalent of q4_1. |
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## q4_2 compatibility |
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q4_2 is a relatively new 4bit quantisation method offering improved quality. However they are still under development and their formats are subject to change. |
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In order to use these files you will need to use recent llama.cpp code. And it's possible that future updates to llama.cpp could require that these files are re-generated. |
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If and when the q4_2 file no longer works with recent versions of llama.cpp I will endeavour to update it. |
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If you want to ensure guaranteed compatibility with a wide range of llama.cpp versions, use the q4_0 file. |
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## q5_0 and q5_1 compatibility |
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These new methods were released to llama.cpp on 26th April. You will need to pull the latest llama.cpp code and rebuild to be able to use them. |
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Don't expect any third-party UIs/tools to support them yet. |
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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 12 -m GPT4All-13B-snoozy.q4_2.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "Below is an instruction that describes a task. Write a response that appropriately completes the request. |
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### Instruction: |
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Write a story about llamas |
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### Response:" |
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``` |
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Change `-t 12` 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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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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Note: at this time text-generation-webui will not support the new q5 quantisation methods. |
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**Thireus** has written a [great guide on how to update it to the latest llama.cpp code](https://huggingface.co/TheBloke/wizardLM-7B-GGML/discussions/5) so that these files can be used in the UI. |
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## Repositories available |
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* [4bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/GPT4ALL-13B-snoozy-GPTQ). |
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* [4bit and 5bit GGML models for GPU inference](https://huggingface.co/TheBloke/GPT4ALL-13B-snoozy-GGML). |
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* [Nomic.AI's original model in float32 HF for GPU inference](https://huggingface.co/nomic-ai/gpt4all-13b-snoozy). |
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# Original Model Card for GPT4All-13b-snoozy |
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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. |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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This model has been finetuned from LLama 13B |
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- **Developed by:** [Nomic AI](https://home.nomic.ai) |
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- **Model Type:** A finetuned LLama 13B model on assistant style interaction data |
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- **Language(s) (NLP):** English |
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- **License:** Apache-2 |
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- **Finetuned from model [optional]:** LLama 13B |
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This model was trained on `nomic-ai/gpt4all-j-prompt-generations` using `revision=v1.3-groovy` |
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### Model Sources [optional] |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** [https://github.com/nomic-ai/gpt4all](https://github.com/nomic-ai/gpt4all) |
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- **Base Model Repository:** [https://github.com/facebookresearch/llama](https://github.com/facebookresearch/llama) |
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- **Demo [optional]:** [https://gpt4all.io/](https://gpt4all.io/) |
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### Results |
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Results on common sense reasoning benchmarks |
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``` |
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Model BoolQ PIQA HellaSwag WinoGrande ARC-e ARC-c OBQA |
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----------------------- ---------- ---------- ----------- ------------ ---------- ---------- ---------- |
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GPT4All-J 6B v1.0 73.4 74.8 63.4 64.7 54.9 36.0 40.2 |
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GPT4All-J v1.1-breezy 74.0 75.1 63.2 63.6 55.4 34.9 38.4 |
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GPT4All-J v1.2-jazzy 74.8 74.9 63.6 63.8 56.6 35.3 41.0 |
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GPT4All-J v1.3-groovy 73.6 74.3 63.8 63.5 57.7 35.0 38.8 |
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GPT4All-J Lora 6B 68.6 75.8 66.2 63.5 56.4 35.7 40.2 |
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GPT4All LLaMa Lora 7B 73.1 77.6 72.1 67.8 51.1 40.4 40.2 |
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GPT4All 13B snoozy *83.3* 79.2 75.0 *71.3* 60.9 44.2 43.4 |
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Dolly 6B 68.8 77.3 67.6 63.9 62.9 38.7 41.2 |
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Dolly 12B 56.7 75.4 71.0 62.2 *64.6* 38.5 40.4 |
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Alpaca 7B 73.9 77.2 73.9 66.1 59.8 43.3 43.4 |
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Alpaca Lora 7B 74.3 *79.3* 74.0 68.8 56.6 43.9 42.6 |
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GPT-J 6B 65.4 76.2 66.2 64.1 62.2 36.6 38.2 |
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LLama 7B 73.1 77.4 73.0 66.9 52.5 41.4 42.4 |
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LLama 13B 68.5 79.1 *76.2* 70.1 60.0 *44.6* 42.2 |
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Pythia 6.9B 63.5 76.3 64.0 61.1 61.3 35.2 37.2 |
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Pythia 12B 67.7 76.6 67.3 63.8 63.9 34.8 38.0 |
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Vicuña T5 81.5 64.6 46.3 61.8 49.3 33.3 39.4 |
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Vicuña 13B 81.5 76.8 73.3 66.7 57.4 42.7 43.6 |
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Stable Vicuña RLHF 82.3 78.6 74.1 70.9 61.0 43.5 *44.4* |
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StableLM Tuned 62.5 71.2 53.6 54.8 52.4 31.1 33.4 |
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StableLM Base 60.1 67.4 41.2 50.1 44.9 27.0 32.0 |
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``` |
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