Instructions to use jondurbin/airoboros-l2-70b-gpt4-1.4.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jondurbin/airoboros-l2-70b-gpt4-1.4.1 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="jondurbin/airoboros-l2-70b-gpt4-1.4.1")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jondurbin/airoboros-l2-70b-gpt4-1.4.1")
model = AutoModelForCausalLM.from_pretrained("jondurbin/airoboros-l2-70b-gpt4-1.4.1", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jondurbin/airoboros-l2-70b-gpt4-1.4.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jondurbin/airoboros-l2-70b-gpt4-1.4.1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jondurbin/airoboros-l2-70b-gpt4-1.4.1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/jondurbin/airoboros-l2-70b-gpt4-1.4.1

SGLang

How to use jondurbin/airoboros-l2-70b-gpt4-1.4.1 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 "jondurbin/airoboros-l2-70b-gpt4-1.4.1" \
    --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": "jondurbin/airoboros-l2-70b-gpt4-1.4.1",
		"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 "jondurbin/airoboros-l2-70b-gpt4-1.4.1" \
        --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": "jondurbin/airoboros-l2-70b-gpt4-1.4.1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use jondurbin/airoboros-l2-70b-gpt4-1.4.1 with Docker Model Runner:
```
docker model run hf.co/jondurbin/airoboros-l2-70b-gpt4-1.4.1
```

Thank you for all the awesome work, Jon.

by ReMeDy-TV - opened Jul 24, 2023

Discussion

ReMeDy-TV

Jul 24, 2023

•

edited Jul 24, 2023

I've been excited to try this model out more than any other post-llama2. Definitely looking forward to putting it thru some action. Airoboros has been a go-to favorite for a lot of people. Thanks again.

algorithm

Jul 24, 2023

Yes, I agree, thank you so much Jon!

Shouyi987

Jul 24, 2023

Me too!
Thank you so much! I've been eagerly waiting for this model ever since the llama 2 announcement.

MB7977

Jul 24, 2023

I'm not quite sure how you do it, but your models are a step above the rest, they really are. Thank you for your work.

jreoka

Jul 30, 2023

These models are fantastic and well rounded. Amazing work. Please keep it up! We all appreciate it so much!

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