Instructions to use aws-neuron/SOLAR-10.7B-v1.0-neuron with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use aws-neuron/SOLAR-10.7B-v1.0-neuron with Transformers:

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

pipe = pipeline("text-generation", model="aws-neuron/SOLAR-10.7B-v1.0-neuron")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("aws-neuron/SOLAR-10.7B-v1.0-neuron")
model = AutoModelForCausalLM.from_pretrained("aws-neuron/SOLAR-10.7B-v1.0-neuron")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use aws-neuron/SOLAR-10.7B-v1.0-neuron with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "aws-neuron/SOLAR-10.7B-v1.0-neuron"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "aws-neuron/SOLAR-10.7B-v1.0-neuron",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/aws-neuron/SOLAR-10.7B-v1.0-neuron

SGLang

How to use aws-neuron/SOLAR-10.7B-v1.0-neuron 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 "aws-neuron/SOLAR-10.7B-v1.0-neuron" \
    --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": "aws-neuron/SOLAR-10.7B-v1.0-neuron",
		"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 "aws-neuron/SOLAR-10.7B-v1.0-neuron" \
        --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": "aws-neuron/SOLAR-10.7B-v1.0-neuron",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use aws-neuron/SOLAR-10.7B-v1.0-neuron with Docker Model Runner:
```
docker model run hf.co/aws-neuron/SOLAR-10.7B-v1.0-neuron
```

jburtoft commited on Sep 5, 2024

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@@ -21,7 +21,7 @@ This model has been exported to the `neuron` format using specific `input_shapes
 It has been compiled to run on an inf2.24xlarge instance on AWS.  Note that while the inf2.24xlarge has 12 cores, this compilation uses 8.  This model and configuration seems to require the cores be a power of 2.
-**This has been compiled using version 2.16 of the Neuron SDK.  Make sure your environment has version 2.16 installed**
 Please refer to the 🤗 `optimum-neuron` [documentation](https://huggingface.co/docs/optimum-neuron/main/en/guides/models#configuring-the-export-of-a-generative-model) for an explanation of these parameters.

 It has been compiled to run on an inf2.24xlarge instance on AWS.  Note that while the inf2.24xlarge has 12 cores, this compilation uses 8.  This model and configuration seems to require the cores be a power of 2.
+**This has been compiled using version 2.16 of the Neuron SDK.  Make sure your environment has version 2.16 installed.  Even better is if you just compile it using the latest SDK**
 Please refer to the 🤗 `optimum-neuron` [documentation](https://huggingface.co/docs/optimum-neuron/main/en/guides/models#configuring-the-export-of-a-generative-model) for an explanation of these parameters.