Instructions to use Corianas/gpt-j-6B-Dolly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Corianas/gpt-j-6B-Dolly with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Corianas/gpt-j-6B-Dolly")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Corianas/gpt-j-6B-Dolly") model = AutoModelForCausalLM.from_pretrained("Corianas/gpt-j-6B-Dolly", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Corianas/gpt-j-6B-Dolly with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Corianas/gpt-j-6B-Dolly" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Corianas/gpt-j-6B-Dolly", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Corianas/gpt-j-6B-Dolly
- SGLang
How to use Corianas/gpt-j-6B-Dolly 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 "Corianas/gpt-j-6B-Dolly" \ --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": "Corianas/gpt-j-6B-Dolly", "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 "Corianas/gpt-j-6B-Dolly" \ --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": "Corianas/gpt-j-6B-Dolly", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Corianas/gpt-j-6B-Dolly with Docker Model Runner:
docker model run hf.co/Corianas/gpt-j-6B-Dolly
G.A.R.Y. (Guided Artificially Resourceful Yes-man)
A clone of Dolly (https://github.com/databrickslabs/dolly)
Trained on 8xa100s over the course of 45 minutes. (total time less than 3 hours with false starts and getting less optimal results while learning how best to proceed.)
license: cc-by-nc-2.0
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 35.1 |
| ARC (25-shot) | 41.3 |
| HellaSwag (10-shot) | 65.97 |
| MMLU (5-shot) | 26.78 |
| TruthfulQA (0-shot) | 37.91 |
| Winogrande (5-shot) | 64.72 |
| GSM8K (5-shot) | 0.91 |
| DROP (3-shot) | 8.1 |
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