metadata
base_model: unsloth/llama-3-8b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
Uploaded model
- Developed by: tykiww
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
Setting up and testing own Endpoint Handler
Sources:
- https://www.philschmid.de/custom-inference-handler
- https://discuss.huggingface.co/t/model-wont-load-on-custom-inference-endpoint/91780
- https://huggingface.co/docs/inference-endpoints/guides/custom_handler
Setup Environment
Install necessary packages to set up and test endpoint handler.
# install git-lfs to interact with the repository
sudo apt-get update
sudo apt-get install git-lfs
# install transformers (not needed for inference since it is installed by default in the container)
pip install transformers[sklearn,sentencepiece,audio,vision]
Clone model weights of interest.
git lfs install
git clone https://huggingface.co/tykiww/llama3-8b-quantized
Login to huggingface
# setup cli with token
huggingface-cli login
git config --global credential.helper store
Confirm login in case you are unsure.
huggingface-cli whoami
Navigate to repo and create a handler.py file
cd llama3-8b-bnb-4bit-lora #&& touch handler.py
Create a requirements.txt file with the following items
huggingface_hub
unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git
xformers
trl<0.9.0
peft==0.11.1
bitsandbytes
transformers==4.41.2 # must use /:
Must have a GPU compatible with Unsloth.