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
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README.md
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@@ -144,7 +144,7 @@ This project would not have been possible without compute generously provided by
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Thanks to everyone who have helped out one way or another (listed alphabetically):
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- [James Bradbury](https://twitter.com/jekbradbury) for valuable assistance with debugging JAX issues.
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- [Stella Biderman](www.stellabiderman.com), [Eric Hallahan](https://twitter.com/erichallahan), [Kurumuz](https://github.com/kurumuz/), and [Finetune](https://github.com/finetuneanon/) for converting the model to be compatible with the `transformers` package.
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- [Leo Gao](https://twitter.com/nabla_theta) for running zero shot evaluations for the baseline models for the table.
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- [Laurence Golding](https://github.com/researcher2/) for adding some features to the web demo.
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- [Aran Komatsuzaki](https://twitter.com/arankomatsuzaki) for advice with experiment design and writing the blog posts.
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Thanks to everyone who have helped out one way or another (listed alphabetically):
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- [James Bradbury](https://twitter.com/jekbradbury) for valuable assistance with debugging JAX issues.
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| 147 |
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- [Stella Biderman](https://www.stellabiderman.com), [Eric Hallahan](https://twitter.com/erichallahan), [Kurumuz](https://github.com/kurumuz/), and [Finetune](https://github.com/finetuneanon/) for converting the model to be compatible with the `transformers` package.
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| 148 |
- [Leo Gao](https://twitter.com/nabla_theta) for running zero shot evaluations for the baseline models for the table.
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| 149 |
- [Laurence Golding](https://github.com/researcher2/) for adding some features to the web demo.
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| 150 |
- [Aran Komatsuzaki](https://twitter.com/arankomatsuzaki) for advice with experiment design and writing the blog posts.
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