These files are not yet cert signed by Windows/Apple so you will see security warnings on initial installation. We did not want to delay release while waiting for their process to complete.
Find the most up-to-date information on the [GPT4All Website](https://gpt4all.io/index.html)
### Raw Model
[ggml Model Download Link](https://pub-7382deb27b3e46cd959cc60ce3efaa5a.r2.dev/ggml-gpt4all-j.bin)
Note this model is only compatible with the C++ bindings found [here](https://github.com/nomic-ai/gpt4all-chat). It will not work with any existing llama.cpp bindings as we had to do a large fork of llama.cpp. GPT4All will support the ecosystem around this new C++ backend going forward.
Python bindings are imminent and will be integrated into this [repository](https://github.com/nomic-ai/pyllamacpp). Stay tuned on the [GPT4All discord](https://discord.gg/mGZE39AS3e) for updates.
- We are releasing the curated training data for anyone to replicate GPT4All-J here: [GPT4All-J Training Data](https://huggingface.co/datasets/nomic-ai/gpt4all-j-prompt-generations)
1. Download the `gpt4all-lora-quantized.bin` file from [Direct Link](https://the-eye.eu/public/AI/models/nomic-ai/gpt4all/gpt4all-lora-quantized.bin) or [[Torrent-Magnet]](https://tinyurl.com/gpt4all-lora-quantized).
2. Clone this repository, navigate to `chat`, and place the downloaded file there.
To run GPT4All in python, see the new [official Python bindings](https://github.com/nomic-ai/pyllamacpp).
The old bindings are still available but now deprecated. They will not work in a notebook environment.
To get running using the python client with the CPU interface, first install the [nomic client](https://github.com/nomic-ai/nomic) using `pip install nomic`
Then, you can use the following script to interact with GPT4All:
```
from nomic.gpt4all import GPT4All
m = GPT4All()
m.open()
m.prompt('write me a story about a lonely computer')
```
## GPU Interface
There are two ways to get up and running with this model on GPU.
The setup here is slightly more involved than the CPU model.
1. clone the nomic client [repo](https://github.com/nomic-ai/nomic) and run `pip install .[GPT4All]` in the home dir.
2. run `pip install nomic` and install the additional deps from the wheels built [here](https://github.com/nomic-ai/nomic/tree/main/bin)
Once this is done, you can run the model on GPU with a script like the following:
```
from nomic.gpt4all import GPT4AllGPU
m = GPT4AllGPU(LLAMA_PATH)
config = {'num_beams': 2,
'min_new_tokens': 10,
'max_length': 100,
'repetition_penalty': 2.0}
out = m.generate('write me a story about a lonely computer', config)
print(out)
```
Where LLAMA_PATH is the path to a Huggingface Automodel compliant LLAMA model.
Nomic is unable to distribute this file at this time.
We are working on a GPT4All that does not have this limitation right now.
You can pass any of the [huggingface generation config params](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.GenerationConfig) in the config.
# GPT4All Compatibility Ecosystem
Edge models in the GPT4All Ecosystem. Please PR as the [community grows](https://huggingface.co/models?sort=modified&search=4bit).
Feel free to convert this to a more structured table.
-<spanstyle="color:green">(Done)</span> [Create a good conversational chat interface for the model.](https://github.com/nomic-ai/gpt4all-ui)
-<spanstyle="color:green">(Done)</span> [Allow users to opt in and submit their chats for subsequent training runs](https://github.com/nomic-ai/gpt4all-ui)
## Medium Term
-<spanstyle="color:red">(NOT STARTED)</span> Integrate GPT4All with [Atlas](https://atlas.nomic.ai) to allow for document retrieval.
- BLOCKED by GPT4All based on GPTJ
-<spanstyle="color:red">(NOT STARTED)</span> Integrate GPT4All with Langchain.
-<spanstyle="color:green">(IN PROGRESS)</span> Build easy custom training scripts to allow users to fine tune models.
## Long Term
-<spanstyle="color:red">(NOT STARTED)</span> Allow anyone to curate training data for subsequent GPT4All releases using Atlas.
> 1. The title of your movie plot should be "The Last Stand".
> 2. The summary of your movie plot should be: A group of mercenaries are hired to protect a small town from a dangerous criminal who is on the run. However, the town's sheriff is not willing to let them take over and decides to take matters into his own hands.
