Finetuned from model : unsloth/llama-3-8b-Instruct-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
README
This is a test model on a the following
a private dataset
slight customization on llama3 template (no new tokens | no new configs)
Works with Ollama create with just "FROM path/to/model" as Modelfile (llama3 template works no issues)
HOW TO USE
The whole point of conversion for me was I wanted to be able to to use it through Ollama or (other local options)
For Ollama, it required to be a GGUF file. Once you have this it is pretty straight forward (if it is in llama3 which this model is)
Quick Start:
You must already have Ollama running in your setting
Download the unsloth.Q4_K_M.gguf model from Files
In the same directory create a file call "Modelfile"
Inside the "Modelfile" type
python
1FROM ./unsloth.Q4_K_M.gguf
2
Save a go back to the folder (folder where model + Modelfile exisit)
Now in terminal make sure you are in the same location of the folder and type in the following command
ollama create mycustomai # "mycustomai" <- you can name it anything u want
This GGUF is based on llama3-3-8B-Instruct thus ollama doesn't need anything else to auto configure this model
After than you should be able to use this model to chat!
Model is also available in Ollama
deeokay/minillama -> Q2_K version
deeokay/mediumllama -> Q3_K_M version
deeokay/customllama -> Q4_K_M version
In the terminal just
ollama pull deeokay/customllama
and you can use the model.
NOTE: DISCLAIMER
Please note this is not for the purpose of production, but result of Fine Tuning through self learning
The llama3 Special Tokens where kept the same, however the format was slight customized using the available tokens
I have foregone the {{.System}} part as this would be updated when converting the llama3.
I wanted to test if the model would understand additional headers that I created such as what my datasets has
Analaysis, Classification, Sentiment
Mulitple pass through my ~70K personalized customized dataset.