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| presets | 3 lat temu | |
| LICENSE | 3 lat temu | |
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| convert-to-torch.py | 3 lat temu | |
| download-model.py | 3 lat temu | |
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| requirements.txt | 3 lat temu | |
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A gradio webui for running large language models locally. Supports gpt-j-6B, gpt-neox-20b, opt, galactica, and many others.
Its goal is to become the AUTOMATIC1111/stable-diffusion-webui of text generation.
Create a conda environment:
conda create -n textgen
conda activate textgen
Install the appropriate pytorch for your GPU. For NVIDIA GPUs, this should work:
conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia
Install the requirements:
pip install -r requirements.txt
Models should be placed under models/model-name. For instance, models/gpt-j-6B for gpt-j-6B.
Hugging Face is the main place to download models. These are some of my favorite:
The files that you need to download are the json, txt, and pytorch*.bin files. The remaining files are not necessary.
For your convenience, you can automatically download a model from HF using the script download-model.py. Its usage is very simple:
python download-model.py organization/model
For instance:
python download-model.py facebook/opt-1.3b
GPT-4chan has been shut down from Hugging Face, so you need to download it elsewhere. You have two options:
Then follow these steps to install:
models/gpt4chan_model_float16 or models/gpt4chan_modelmodels/gpt-j-6B: python download-model.py EleutherAI/gpt-j-6BThe script convert-to-torch.py allows you to convert models to .pt format, which is about 10x faster to load:
python convert-to-torch.py models/model-name
The output model will be saved to torch-dumps/model-name.pt. When you load a new model, the webui first looks for this .pt file; if it is not found, it loads the model as usual from models/model-name.
conda activate textgen
python server.py
Then browse to
http://localhost:7860/?__theme=dark
Optionally, you can use the following command-line flags:
-h, --help show this help message and exit
--model MODEL Name of the model to load by default.
--notebook Launch the webui in notebook mode, where the output is written to the same text
box as the input.
--chat Launch the webui in chat mode.
--cpu Use the CPU to generate text.
--auto-devices Automatically split the model across the available GPU(s) and CPU.
--load-in-8bit Load the model with 8-bit precision.
--no-listen Make the webui unreachable from your local network.
Inference settings presets can be created under presets/ as text files. These files are detected automatically at startup.
Check the wiki for some examples of VRAM and RAM usage in both GPU and CPU mode.
Pull requests, suggestions and issue reports are welcome.
Make sure to also check out the great work by KoboldAI. I have borrowed some of the presets listed on their wiki after performing a k-means clustering analysis to select the most relevant subsample.