Instructions to use DavidAU/L3-DARKEST-PLANET-16.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DavidAU/L3-DARKEST-PLANET-16.5B with Transformers:

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

pipe = pipeline("text-generation", model="DavidAU/L3-DARKEST-PLANET-16.5B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DavidAU/L3-DARKEST-PLANET-16.5B")
model = AutoModelForCausalLM.from_pretrained("DavidAU/L3-DARKEST-PLANET-16.5B", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use DavidAU/L3-DARKEST-PLANET-16.5B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DavidAU/L3-DARKEST-PLANET-16.5B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DavidAU/L3-DARKEST-PLANET-16.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/DavidAU/L3-DARKEST-PLANET-16.5B

SGLang

How to use DavidAU/L3-DARKEST-PLANET-16.5B 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 "DavidAU/L3-DARKEST-PLANET-16.5B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DavidAU/L3-DARKEST-PLANET-16.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "DavidAU/L3-DARKEST-PLANET-16.5B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DavidAU/L3-DARKEST-PLANET-16.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use DavidAU/L3-DARKEST-PLANET-16.5B with Docker Model Runner:
```
docker model run hf.co/DavidAU/L3-DARKEST-PLANET-16.5B
```

L3-DARKEST-PLANET-16.5B / README.md

DavidAU

Create README.md

67b5a53 verified almost 2 years ago

658 Bytes

library_name: transformers
tags:
  - mergekit
  - merge
base_model: []

L3-DARKEST-PLANET-16.5B

This repo contains the full precision source code, in "safe tensors" format to generate GGUFs, GPTQ, EXL2, AWQ, HQQ and other formats. The source code can also be used directly.

For full information about this model, including:

Details about this model and its use case(s).
Context limits
Special usage notes / settings.
Any model(s) used to create this model.
Template(s) used to access/use this model.
Example generation(s)
GGUF quants of this model

Please go to:

[ https://huggingface.co/DavidAU/L3-DARKEST-PLANET-16.5B-GGUF ]