Instructions to use TehVenom/Dolly_GPT-J-6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TehVenom/Dolly_GPT-J-6b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TehVenom/Dolly_GPT-J-6b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TehVenom/Dolly_GPT-J-6b") model = AutoModelForCausalLM.from_pretrained("TehVenom/Dolly_GPT-J-6b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use TehVenom/Dolly_GPT-J-6b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TehVenom/Dolly_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": "TehVenom/Dolly_GPT-J-6b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TehVenom/Dolly_GPT-J-6b
- SGLang
How to use TehVenom/Dolly_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 "TehVenom/Dolly_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": "TehVenom/Dolly_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 "TehVenom/Dolly_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": "TehVenom/Dolly_GPT-J-6b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TehVenom/Dolly_GPT-J-6b with Docker Model Runner:
docker model run hf.co/TehVenom/Dolly_GPT-J-6b
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Check out the documentation for more information.
This is a merge of the Dolly LoRA with the main GPT-J-6B model, allowing users to use Dolly without having to worry about PEFT dependencies.
This hopes to be as similar as Alpaca, but without requirimg LLaMA access.
The performance is good but not as good as the orginal Alpaca trained from a base model of LLaMa
This is mostly due to the LLaMa 7B model being pretrained on 1T tokens and GPT-J-6B being trained on 300-400M tokens.
- LoRA originally trained by samwit, in: https://huggingface.co/samwit/dolly-lora
- The dataset is the cleaned version of the Alpaca dataset - https://github.com/gururise/AlpacaDataCleaned
- GPT-J-6b: https://huggingface.co/EleutherAI/gpt-j-6B
- here is a Colab https://colab.research.google.com/drive/1O1JjyGaC300BgSJoUbru6LuWAzRzEqCz?usp=sharing
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