llama2-wrapper 0.1.7

Use llama2-wrapper as your local llama2 backend for Generative Agents / Apps

llama2-wrapper

Use llama2-wrapper as your local llama2 backend for Generative Agents/Apps, colab example.

Features

• Supporting models: Llama-2-7b/13b/70b, all Llama-2-GPTQ, all Llama-2-GGML ...
• Supporting model backends: tranformers, bitsandbytes(8-bit inference), AutoGPTQ(4-bit inference), llama.cpp
• Demos: Run Llama2 on MacBook Air; Run Llama2 on Colab T4 GPU
• News, Benchmark, Issue Solutions

llama2-wrapper is the backend and part of llama2-webui, which can run any Llama 2 locally with gradio UI on GPU or CPU from anywhere (Linux/Windows/Mac).

Install

pip install llama2-wrapper

Usage

__call__

__call__() is the function to generate text from a prompt.

For example, run ggml llama2 model on CPU, colab example:

from llama2_wrapper import LLAMA2_WRAPPER, get_prompt 
llama2_wrapper = LLAMA2_WRAPPER()
# Default running on backend llama.cpp.
# Automatically downloading model to: ./models/llama-2-7b-chat.ggmlv3.q4_0.bin
prompt = "Do you know Pytorch"
# llama2_wrapper() will run __call__()
answer = llama2_wrapper(get_prompt(prompt), temperature=0.9)

Run gptq llama2 model on Nvidia GPU, colab example:

from llama2_wrapper import LLAMA2_WRAPPER 
llama2_wrapper = LLAMA2_WRAPPER(backend_type="gptq")
# Automatically downloading model to: ./models/Llama-2-7b-Chat-GPTQ

Run llama2 7b with bitsandbytes 8 bit with a model_path:

from llama2_wrapper import LLAMA2_WRAPPER 
llama2_wrapper = LLAMA2_WRAPPER(
	model_path = "./models/Llama-2-7b-chat-hf",
  backend_type = "transformers",
  load_in_8bit = True
)

generate

generate() is the function to create a generator of response from a prompt.

This is useful when you want to stream the output like typing in the chatbot.

llama2_wrapper = LLAMA2_WRAPPER()
prompt = get_prompt("Hi do you know Pytorch?")
for response in llama2_wrapper.generate(prompt):
	print(response)

The response will be like:

Yes, 
Yes, I'm 
Yes, I'm familiar 
Yes, I'm familiar with 
Yes, I'm familiar with PyTorch! 
...

run

run() is similar to generate(), but run()can also accept chat_historyand system_prompt from the users.

It will process the input message to llama2 prompt template with chat_history and system_prompt for a chatbot-like app.

get_prompt

get_prompt() will process the input message to llama2 prompt with chat_history and system_promptfor chatbot.

By default, chat_history and system_prompt are empty and get_prompt() will add llama2 prompt template to your message:

prompt = get_prompt("Hi do you know Pytorch?")

prompt will be:

[INST] <<SYS>>

<</SYS>>

Hi do you know Pytorch? [/INST]

If use get_prompt("Hi do you know Pytorch?", system_prompt="You are a helpful..."):

[INST] <<SYS>>
You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe.  Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.
<</SYS>>

Hi do you know Pytorch? [/INST]