Instructions to use upstage/Llama-2-70b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use upstage/Llama-2-70b-instruct with Transformers:

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

pipe = pipeline("text-generation", model="upstage/Llama-2-70b-instruct")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("upstage/Llama-2-70b-instruct")
model = AutoModelForCausalLM.from_pretrained("upstage/Llama-2-70b-instruct")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use upstage/Llama-2-70b-instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "upstage/Llama-2-70b-instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "upstage/Llama-2-70b-instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/upstage/Llama-2-70b-instruct

SGLang

How to use upstage/Llama-2-70b-instruct 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 "upstage/Llama-2-70b-instruct" \
    --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": "upstage/Llama-2-70b-instruct",
		"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 "upstage/Llama-2-70b-instruct" \
        --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": "upstage/Llama-2-70b-instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use upstage/Llama-2-70b-instruct with Docker Model Runner:
```
docker model run hf.co/upstage/Llama-2-70b-instruct
```

I want to generate a PowerShell Script Using LLama 2 70b instruct, the output is not accurate

by Mohsin07 - opened Dec 7, 2023

Discussion

Mohsin07

Dec 7, 2023

Prompt I used: Generate a Powershell code to retrive and display details of Azure VMs from multiple Azure Subscriptions, Resourcegroups or hostpools. Include parameters clientid, clientkey, tenant for any authentication details needed for the operations.

Please suggest any changes in prompt or Model that I can get accurate results

Thanks and regards,
Mohsin.

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