Instructions to use EleutherAI/gpt-j-6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EleutherAI/gpt-j-6b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="EleutherAI/gpt-j-6b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6b") model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-j-6b") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use EleutherAI/gpt-j-6b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "EleutherAI/gpt-j-6b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EleutherAI/gpt-j-6b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/EleutherAI/gpt-j-6b
- SGLang
How to use EleutherAI/gpt-j-6b with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "EleutherAI/gpt-j-6b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EleutherAI/gpt-j-6b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "EleutherAI/gpt-j-6b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EleutherAI/gpt-j-6b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use EleutherAI/gpt-j-6b with Docker Model Runner:
docker model run hf.co/EleutherAI/gpt-j-6b
How to fine tune or train with our own data?
Hi,
I am a data engineer and pretty new to AI models. I am interested in building something with my work confluence page information for our internal chatbot for work. The use case is instead of searching the whole confluence for some details, it should answer like chatGPT.
Here are my questions?
- Can I do this with gpt-j-6b or suggest another model?
- What are the steps to fine-tune? Could someone point out if there is any existing codebase to do that?
Appreciate any help in this regard.
Thanks,
Ram
This video provides some information. Let us know how you fare.
https://www.youtube.com/watch?v=efPrtcLdcdM
Some of the links referenced:
https://github.com/yk/gpt-4chan-public
His code
https://zenodo.org/record/3606810#.YpjGgexByDU
Data set
The model ( no longer available): https://huggingface.co/ykilcher/gpt-4chan
Hi @ram77gowri were you able to fine-tune the gptj model?
@hsuyab Not yet, Got side tracked with some other work. Getting back again.