Instructions to use OpenAssistant/falcon-40b-sft-mix-1226 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OpenAssistant/falcon-40b-sft-mix-1226 with Transformers:

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

pipe = pipeline("text-generation", model="OpenAssistant/falcon-40b-sft-mix-1226", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("OpenAssistant/falcon-40b-sft-mix-1226", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use OpenAssistant/falcon-40b-sft-mix-1226 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OpenAssistant/falcon-40b-sft-mix-1226"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OpenAssistant/falcon-40b-sft-mix-1226",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/OpenAssistant/falcon-40b-sft-mix-1226

SGLang

How to use OpenAssistant/falcon-40b-sft-mix-1226 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 "OpenAssistant/falcon-40b-sft-mix-1226" \
    --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": "OpenAssistant/falcon-40b-sft-mix-1226",
		"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 "OpenAssistant/falcon-40b-sft-mix-1226" \
        --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": "OpenAssistant/falcon-40b-sft-mix-1226",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use OpenAssistant/falcon-40b-sft-mix-1226 with Docker Model Runner:
```
docker model run hf.co/OpenAssistant/falcon-40b-sft-mix-1226
```

Which Azure VM can run the model?

by AbRds - opened Jul 10, 2023

Discussion

AbRds

Jul 10, 2023

Hi everyone,

We are thinking on running this model in an Azure VM, but we are not sure which one to choose. Somebody has tested the model on Azure?
We have three possible VM, any recommendation?

NC24ads_A100_v4 24vCPU, 220GB RAM, 80GB GPU Memory
NC64as_T4_v3 64vCPU, 440GB RAM, 64GB GPU Memory
ND24s 24vCPU, 440GB RAM, 96GB GPU Memory

Thanks in advance

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