Instructions to use stabilityai/StableBeluga2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use stabilityai/StableBeluga2 with Transformers:

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

pipe = pipeline("text-generation", model="stabilityai/StableBeluga2")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("stabilityai/StableBeluga2")
model = AutoModelForMultimodalLM.from_pretrained("stabilityai/StableBeluga2")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use stabilityai/StableBeluga2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "stabilityai/StableBeluga2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "stabilityai/StableBeluga2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/stabilityai/StableBeluga2

SGLang

How to use stabilityai/StableBeluga2 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 "stabilityai/StableBeluga2" \
    --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": "stabilityai/StableBeluga2",
		"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 "stabilityai/StableBeluga2" \
        --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": "stabilityai/StableBeluga2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use stabilityai/StableBeluga2 with Docker Model Runner:
```
docker model run hf.co/stabilityai/StableBeluga2
```

dmayhem93 commited on Jul 27, 2023

Commit

5187e8d

1 Parent(s): 45efbd5

Update README.md

Browse files

Files changed (1) hide show

README.md +6 -6

README.md CHANGED Viewed

@@ -12,11 +12,11 @@ pipeline_tag: text-generation
 ## Model Description
-`FreeWilly2` is a Llama2 70B model finetuned on an Orca style Dataset
 ## Usage
-Start chatting with `FreeWilly2` using the following code snippet:
 ```python
 import torch
@@ -43,21 +43,21 @@ This is a system prompt, please behave and help the user.
 Your prompt here
 ### Assistant
-The output of FreeWilly2
 ```
 ## Model Details
 * **Developed by**: [Stability AI](https://stability.ai/)
-* **Model type**: FreeWilly is an auto-regressive language model fine-tuned on Llama2 70B.
 * **Language(s)**: English
 * **Library**: [HuggingFace Transformers](https://github.com/huggingface/transformers)
-* **License**: Fine-tuned checkpoints (`FreeWilly2`) is licensed under the Non-Commercial Creative Commons license ([CC BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/))
 * **Contact**: For questions and comments about the model, please email `lm@stability.ai`
 ### Training Dataset
-`FreeWilly2` is trained on our internal Orca-style dataset
 ### Training Procedure

 ## Model Description
+`Stable Beluga 2` is a Llama2 70B model finetuned on an Orca style Dataset
 ## Usage
+Start chatting with `Stable Beluga 2` using the following code snippet:
 ```python
 import torch
 Your prompt here
 ### Assistant
+The output of Stable Beluga 2
 ```
 ## Model Details
 * **Developed by**: [Stability AI](https://stability.ai/)
+* **Model type**: Stable Beluga 2 is an auto-regressive language model fine-tuned on Llama2 70B.
 * **Language(s)**: English
 * **Library**: [HuggingFace Transformers](https://github.com/huggingface/transformers)
+* **License**: Fine-tuned checkpoints (`Stable Beluga 2`) is licensed under the [STABLE BELUGA NON-COMMERCIAL COMMUNITY LICENSE AGREEMENT](https://huggingface.co/stabilityai/StableBeluga2/LICENSE.TXT)
 * **Contact**: For questions and comments about the model, please email `lm@stability.ai`
 ### Training Dataset
+` Stable Beluga 2` is trained on our internal Orca-style dataset
 ### Training Procedure