| Quantization made by Richard Erkhov. | |
| [Github](https://github.com/RichardErkhov) | |
| [Discord](https://discord.gg/pvy7H8DZMG) | |
| [Request more models](https://github.com/RichardErkhov/quant_request) | |
| gpt4all-j - bnb 4bits | |
| - Model creator: https://huggingface.co/nomic-ai/ | |
| - Original model: https://huggingface.co/nomic-ai/gpt4all-j/ | |
| Original model description: | |
| --- | |
| license: apache-2.0 | |
| datasets: | |
| - nomic-ai/gpt4all-j-prompt-generations | |
| language: | |
| - en | |
| pipeline_tag: text-generation | |
| --- | |
| # Model Card for GPT4All-J | |
| 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 | |
| <!-- Provide a longer summary of what this model is. --> | |
| This model has been finetuned from [GPT-J](https://huggingface.co/EleutherAI/gpt-j-6B) | |
| - **Developed by:** [Nomic AI](https://home.nomic.ai) | |
| - **Model Type:** A finetuned GPT-J model on assistant style interaction data | |
| - **Language(s) (NLP):** English | |
| - **License:** Apache-2 | |
| - **Finetuned from model [optional]:** [GPT-J](https://huggingface.co/EleutherAI/gpt-j-6B) | |
| We have released several versions of our finetuned GPT-J model using [different dataset versions](https://huggingface.co/datasets/nomic-ai/gpt4all-j-prompt-generations) | |
| - v1.0: The original model trained on the v1.0 dataset | |
| - v1.1-breezy: Trained on afiltered dataset where we removed all instances of AI language model | |
| - v1.2-jazzy: Trained on a filtered dataset where we also removed instances like I'm sorry, I can't answer... and AI language model | |
| - v1.3-groovy: We added Dolly and ShareGPT to the v1.2 dataset and removed ~8% of the dataset in v1.2 that contained semantic duplicates using [Atlas](https://atlas.nomic.ai/). | |
| To download a model with a specific revision run | |
| ```python | |
| from transformers import AutoModelForCausalLM | |
| model = AutoModelForCausalLM.from_pretrained("nomic-ai/gpt4all-j", revision="v1.2-jazzy") | |
| ``` | |
| Downloading without specifying `revision` defaults to `main`/`v1.0`. | |
| ### Model Sources [optional] | |
| <!-- Provide the basic links for the model. --> | |
| - **Repository:** [https://github.com/nomic-ai/gpt4all](https://github.com/nomic-ai/gpt4all) | |
| - **Base Model Repository:** [https://github.com/kingoflolz/mesh-transformer-jax](https://github.com/kingoflolz/mesh-transformer-jax) | |
| - **Paper [optional]:** [GPT4All-J: An Apache-2 Licensed Assistant-Style Chatbot](https://s3.amazonaws.com/static.nomic.ai/gpt4all/2023_GPT4All-J_Technical_Report_2.pdf) | |
| - **Demo [optional]:** [https://gpt4all.io/](https://gpt4all.io/) | |
| ### Training Procedure | |
| GPT4All is made possible by our compute partner [Paperspace](https://www.paperspace.com/). | |
| Trained on a DGX cluster with 8 A100 80GB GPUs for ~12 hours. Using Deepspeed + Accelerate, we use a global batch size of 256 with a learning rate of 2e-5. More information can be found in the repo. | |
| ### Results | |
| Results on common sense reasoning benchmarks | |
| ``` | |
| | Model | BoolQ | PIQA | HellaSwag | WinoGrande | ARC-e | ARC-c | OBQA | Avg. | | |
| |:--------------------------|:--------:|:--------:|:---------:|:----------:|:--------:|:--------:|:--------:|:--------:| | |
| | GPT4All-J 6B v1.0 | 73.4 | 74.8 | 63.4 | 64.7 | 54.9 | 36.0 | 40.2 | 58.2 | | |
| | GPT4All-J v1.1-breezy | 74.0 | 75.1 | 63.2 | 63.6 | 55.4 | 34.9 | 38.4 | 57.8 | | |
| | GPT4All-J v1.2-jazzy | 74.8 | 74.9 | 63.6 | 63.8 | 56.6 | 35.3 | 41.0 | 58.6 | | |
| | GPT4All-J v1.3-groovy | 73.6 | 74.3 | 63.8 | 63.5 | 57.7 | 35.0 | 38.8 | 58.1 | | |
| | GPT4All-J Lora 6B | 68.6 | 75.8 | 66.2 | 63.5 | 56.4 | 35.7 | 40.2 | 58.1 | | |
| | GPT4All LLaMa Lora 7B | 73.1 | 77.6 | 72.1 | 67.8 | 51.1 | 40.4 | 40.2 | 60.3 | | |
| | GPT4All 13B snoozy | **83.3** | 79.2 | 75.0 | **71.3** | 60.9 | 44.2 | 43.4 | **65.3** | | |
| | Dolly 6B | 68.8 | 77.3 | 67.6 | 63.9 | 62.9 | 38.7 | 41.2 | 60.1 | | |
| | Dolly 12B | 56.7 | 75.4 | 71.0 | 62.2 | 64.6 | 38.5 | 40.4 | 58.4 | | |
| | Alpaca 7B | 73.9 | 77.2 | 73.9 | 66.1 | 59.8 | 43.3 | 43.4 | 62.4 | | |
| | Alpaca Lora 7B | 74.3 | **79.3** | 74.0 | 68.8 | 56.6 | 43.9 | 42.6 | 62.8 | | |
| | GPT-J 6.7B | 65.4 | 76.2 | 66.2 | 64.1 | 62.2 | 36.6 | 38.2 | 58.4 | | |
| | LLama 7B | 73.1 | 77.4 | 73.0 | 66.9 | 52.5 | 41.4 | 42.4 | 61.0 | | |
| | LLama 13B | 68.5 | 79.1 | 76.2 | 70.1 | 60.0 | **44.6** | 42.2 | 63.0 | | |
| | Pythia 6.7B | 63.5 | 76.3 | 64.0 | 61.1 | 61.3 | 35.2 | 37.2 | 57.0 | | |
| | Pythia 12B | 67.7 | 76.6 | 67.3 | 63.8 | 63.9 | 34.8 | 38 | 58.9 | | |
| | Fastchat T5 | 81.5 | 64.6 | 46.3 | 61.8 | 49.3 | 33.3 | 39.4 | 53.7 | | |
| | Fastchat Vicuña 7B | 76.6 | 77.2 | 70.7 | 67.3 | 53.5 | 41.2 | 40.8 | 61.0 | | |
| | Fastchat Vicuña 13B | 81.5 | 76.8 | 73.3 | 66.7 | 57.4 | 42.7 | 43.6 | 63.1 | | |
| | StableVicuña RLHF | 82.3 | 78.6 | 74.1 | 70.9 | 61.0 | 43.5 | **44.4** | 65.0 | | |
| | StableLM Tuned | 62.5 | 71.2 | 53.6 | 54.8 | 52.4 | 31.1 | 33.4 | 51.3 | | |
| | StableLM Base | 60.1 | 67.4 | 41.2 | 50.1 | 44.9 | 27.0 | 32.0 | 42.2 | | |
| | Koala 13B | 76.5 | 77.9 | 72.6 | 68.8 | 54.3 | 41.0 | 42.8 | 62.0 | | |
| | Open Assistant Pythia 12B | 67.9 | 78.0 | 68.1 | 65.0 | 64.2 | 40.4 | 43.2 | 61.0 | | |
| | Mosaic mpt-7b | 74.8 | **79.3** | **76.3** | 68.6 | **70.0** | 42.2 | 42.6 | 64.8 | | |
| | text-davinci-003 | 88.1 | 83.8 | 83.4 | 75.8 | 83.9 | 63.9 | 51.0 | 75.7 | | |
| ``` | |