Download the CPU quantized gpt4all model checkpoint: [gpt4all-lora-quantized.bin](https://the-eye.eu/public/AI/models/nomic-ai/gpt4all/gpt4all-lora-quantized.bin) - [[Torrent-Magnet]](magnet:?xt=urn:btih:EE5150157050CB5D1979669A1EA14FC2C4C3692E&dn=gpt4all-lora-quantized.bin&tr=udp%3a%2f%2ftracker.openbittorrent.com%3a80%2fannounce&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce)
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 GPU4All:
```
from nomic import GPT4All
m = GPT4All()
m.connect()
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 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.
# Roadmap
## Short Term
-<spanstyle="color:green">(IN PROGRESS)</span> Train a GPT4All model based on GPTJ to alleviate llama distribution issues.
-<spanstyle="color:green">(IN PROGRESS)</span> Create improved CPU and GPU interfaces for this model.
### Provide instructions for the given exercise. Leg Raises
>Leg Raises
>1. Stand with your feet shoulder-width apart and your knees slightly bent.
>2. Raise your arms straight out in front of you.
>3. Slowly bend your knees and raise your heels off the ground.
>4. Hold this position for a count of 3, then slowly lower your heels back to the ground.
>5. Repeat the exercise 10 times.
>6. Do not let your knees go beyond your toes.
>7. Keep your back straight and your abdominal muscles engaged.
>8. Do not let your hips sag or your back arch.
>9. Keep your arms straight and your elbows locked.
>10. Do not let your head drop or your shoulders rise.
>11. Breathe normally throughout the exercise.
>12. Rest for 30 seconds before repeating the exercise.
>13. Gradually increase the number of repetitions as you become stronger.
### A color description has been provided. Find the CSS code associated with that color. A light red color with a medium light shade of pink
>The CSS code associated with the color provided is: #FF6347
### Come up with an interesting idea for a new movie plot. Your plot should be described with a title and a summary.
>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.
