A Jupyter kernel using LLM models from Huggingface
Project description
chatbot_kernel
A Jupyter kernel to use Jupyter as a chat window, running downloaded LLMs locally.
Installation
This kernel package can be install from PyPI
$ pip install chatbot_kernel
Once the package installed, the kernel spec can be installed to home directory by command:
$ python -m chatbot_kernel install --user
If you are using virtualenv, do
$ python -m chatbot_kernel install --sys-prefix
instead.
If you install the package to a virtual environment, you may need to set up JUPYTER_PATH=/path/to/venv/share/jupyter:$JUPYTER_PATH
so that jupyter can find the kernel
Usage
A few magics are available in the kernel:
%help
: Print help messages%config
: Set advanced configuration. See more in%config help
%load
: Load a pretrained LLM%hf_home
: Set the path to find downloaded LLMs, similar to setHF_HOME
environment variable%model_list
: Show the available LLMs%new_chat
: Clean up the chat history
Before start chatting, you need to at least download a model from HuggingFace. For example, huggingface-cli download meta-llama/Meta-Llama-3-8B-Instruct
.
Once models are downloaded, launch a jupyter notebook/lab and execute %load <model>
and start chatting. Here is an example:
%load meta-llama/Meta-Llama-3-8B-Instruct
hi
who are you
Caveat
Currently, the kernel use the AutoModelForCausalLM
and it is not supported by all models.
A few models have been tested:
meta-llama/Meta-Llama-3-8B-Instruct
mistralai/Mistral-7B-Instruct-v0.3
: needssentencepiece
dependencyunsloth/llama-3-8b-Instruct-bnb-4bit
: needsbitsandbytes
dependency
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