dynamic_prompting
Dynamic Few-Shot Prompting is a Python package that dynamically selects N samples that are contextually close to the user's task or query from a knowledge base (similar to RAG) to include in the prompt.
DynamicPrompting
Key Features
- Faster than fine-tuning a LLM
- Better performance than static few-shot prompts
- Works with less data than fine-tuning a model
Quick Start
With pip:
pip install dynamic_prompting
or install from source
git clone https://github.com/ElmiraGhorbani/dynamic_prompting
pip install -e .
Inference
First setup the model:
Llama3 Model
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Visit the Meta Llama website(https://llama.meta.com/llama-downloads) and register to download the model/s.
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Once registered, you will get an email with a URL to download the models. You will need this URL when you run the download.sh script.
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Once you get the email, navigate to your downloaded llama repository and run the download.sh script.
- Make sure to grant execution permissions to the download.sh script
- During this process, you will be prompted to enter the URL from the email.
- Do not use the “Copy Link” option; copy the link from the email manually.
Once you have downloaded the models, put them in this folder.
otherwise you can use this way:
- Step 1: Go to your Hugging Face account “Settings” and then “Access Tokens” on the left column, and copy the token you need.
- Step 2: On your terminal, export your token starting with “HF_”. Use a distinct name (for example, HF_TOKEN) for each token you export.
You may add this line to your ~/.bashrc if you do not want to export it every time you start a session.
export HF_TOKEN="HF_XXXXXXXXXXXXX"
Text embedding models
The Embeddings class is designed for interfacing with text embedding models. There are many embedding model providers (OpenAI, Cohere, Hugging Face, etc.). Currently, this class provides a standard interface for mxbai-embed-large-v1, bge-small-en-v1.5, and nomic-embed-text-v1.5.
Get started
To start, download the models and put them in this folder.
git lfs install
Nomic Model
git clone https://huggingface.co/nomic-ai/nomic-embed-text-v1.5
cd nomic-embed-text-v1.5
git lfs fetch
BGE Model
git clone https://huggingface.co/BAAI/bge-small-en-v1.5
cd bge-small-en-v1.5
git lfs fetch
Mxbai Model
git clone https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1
cd mxbai-embed-large-v1
git lfs fetch
Demo
Check example.ipynb