Instructions to use WhiteRabbitNeo/Trinity-13B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use WhiteRabbitNeo/Trinity-13B with Transformers:

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

pipe = pipeline("text-generation", model="WhiteRabbitNeo/Trinity-13B", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("WhiteRabbitNeo/Trinity-13B", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("WhiteRabbitNeo/Trinity-13B", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use WhiteRabbitNeo/Trinity-13B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "WhiteRabbitNeo/Trinity-13B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "WhiteRabbitNeo/Trinity-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/WhiteRabbitNeo/Trinity-13B

SGLang

How to use WhiteRabbitNeo/Trinity-13B 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 "WhiteRabbitNeo/Trinity-13B" \
    --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": "WhiteRabbitNeo/Trinity-13B",
		"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 "WhiteRabbitNeo/Trinity-13B" \
        --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": "WhiteRabbitNeo/Trinity-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use WhiteRabbitNeo/Trinity-13B with Docker Model Runner:
```
docker model run hf.co/WhiteRabbitNeo/Trinity-13B
```

Ubuntu commited on Jan 6, 2024

Commit

18a24a7

1 Parent(s): 75f1bb1

image added

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@@ -28,13 +28,11 @@ You agree not to use the Model or Derivatives of the Model:
 -	For any use intended to or which has the effect of discriminating against individuals or groups based on legally protected characteristics or categories.
 ```
-# Trinity by WhiteRabbitNeo
-<br>
 ![Trinity](https://huggingface.co/migtissera/Trinity-13B-v1.0/resolve/main/Trinity.png)
-<br>
 Trinity is a coding specific model series that can be used to create autonomous agents. In the future, we will be releasing agent software that uses this model.

 -	For any use intended to or which has the effect of discriminating against individuals or groups based on legally protected characteristics or categories.
 ```
+# Trinity
 ![Trinity](https://huggingface.co/migtissera/Trinity-13B-v1.0/resolve/main/Trinity.png)
 Trinity is a coding specific model series that can be used to create autonomous agents. In the future, we will be releasing agent software that uses this model.