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NexaAI/octo-net-gguf

sourceHugging Facecc-by-nc-4.0updated 2y agoView on Hugging Face
41likes2.7kdownloads
Model Card

Octopus V4-GGUF: Graph of language models

<p align="center">

  • <a href="https://huggingface.co/NexaAIDev/Octopus-v4" target="_blank">Original Model</a>
  • <a href="https://www.nexa4ai.com/" target="_blank">Nexa AI Website</a>
  • <a href="https://github.com/NexaAI/octopus-v4" target="_blank">Octopus-v4 Github</a>
  • <a href="https://arxiv.org/abs/2404.19296" target="_blank">ArXiv</a>
  • <a href="https://huggingface.co/spaces/NexaAIDev/domainllmleaderboard" target="_blank">Domain LLM Leaderbaord</a> </p>

<p align="center" width="100%"> <a><img src="octopus-v4-logo.png" alt="nexa-octopus" style="width: 40%; min-width: 300px; display: block; margin: auto;"></a> </p>

Acknowledgement: We sincerely thank our community members, Mingyuan and Zoey, for their extraordinary contributions to this quantization effort. Please explore Octopus-v4 for our original huggingface model.

Get Started

To run the models, please download them to your local machine using either git clone or Hugging Face Hub

git clone https://huggingface.co/NexaAIDev/octopus-v4-gguf

Run with llama.cpp (Recommended)

  1. 1.Clone and compile:
bash
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
# Compile the source code:
make
  1. 1.Execute the Model:

Run the following command in the terminal:

bash
./main -m ./path/to/octopus-v4-Q4_K_M.gguf -n 256 -p "<|system|>You are a router. Below is the query from the users, please call the correct function and generate the parameters to call the function.<|end|><|user|>Tell me the result of derivative of x^3 when x is 2?<|end|><|assistant|>"

Run with Ollama

Since our models have not been uploaded to the Ollama server, please download the models and manually import them into Ollama by following these steps:

  1. 1.Install Ollama on your local machine. You can also following the guide from Ollama GitHub repository
bash
git clone https://github.com/ollama/ollama.git ollama
  1. 1.Locate the local Ollama directory:
bash
cd ollama
  1. 1.Create a Modelfile in your directory
bash
touch Modelfile
  1. 1.In the Modelfile, include a FROM statement with the path to your local model, and the default parameters:
bash
FROM ./path/to/octopus-v4-Q4_K_M.gguf
PARAMETER temperature 0
PARAMETER num_ctx 1024
PARAMETER stop <nexa_end>
  1. 1.Use the following command to add the model to Ollama:
bash
ollama create octopus-v4-Q4_K_M -f Modelfile
  1. 1.Verify that the model has been successfully imported:
bash
ollama ls
  1. 1.Run the model
bash
ollama run octopus-v4-Q4_K_M "<|system|>You are a router. Below is the query from the users, please call the correct function and generate the parameters to call the function.<|end|><|user|>Tell me the result of derivative of x^3 when x is 2?<|end|><|assistant|>"

Dataset and Benchmark

  • Utilized questions from MMLU to evaluate the performances.
  • Evaluated with the Ollama llm-benchmark method.

Quantized GGUF Models

NameQuant methodBitsSizeRespons (token/second)Use Cases
Octopus-v4.gguf7.64 GB27.64extremely large
Octopus-v4-Q2_K.ggufQ2_K21.42 GB54.20extremely not recommended, high loss
Octopus-v4-Q3_K.ggufQ3_K31.96 GB51.22not recommended
Octopus-v4-Q3KS.ggufQ3KS31.68 GB51.78not very recommended
Octopus-v4-Q3KM.ggufQ3KM31.96 GB50.86not very recommended
Octopus-v4-Q3KL.ggufQ3KL32.09 GB50.05not very recommended
Octopus-v4-Q4_0.ggufQ4_042.18 GB65.76good quality, recommended
Octopus-v4-Q4_1.ggufQ4_142.41 GB69.01slow, good quality, recommended
Octopus-v4-Q4_K.ggufQ4_K42.39 GB55.76slow, good quality, recommended
Octopus-v4-Q4KS.ggufQ4KS42.19 GB53.98high quality, recommended
Octopus-v4-Q4KM.ggufQ4KM42.39 GB58.39some functions loss, not very recommended
Octopus-v4-Q5_0.ggufQ5_052.64 GB61.98slow, good quality
Octopus-v4-Q5_1.ggufQ5_152.87 GB63.44slow, good quality
Octopus-v4-Q5_K.ggufQ5_K52.82 GB58.28moderate speed, recommended
Octopus-v4-Q5KS.ggufQ5KS52.64 GB59.95moderate speed, recommended
Octopus-v4-Q5KM.ggufQ5KM52.82 GB53.31fast, good quality, recommended
Octopus-v4-Q6_K.ggufQ6_K63.14 GB52.15large, not very recommended
Octopus-v4-Q8_0.ggufQ8_084.06 GB50.10very large, good quality
Octopus-v4-f16.gguff16167.64 GB30.61extremely large

Quantized with llama.cpp