Instructions to use TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1 with Transformers:

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

pipe = pipeline("text-generation", model="TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1")
model = AutoModelForCausalLM.from_pretrained("TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1

SGLang

How to use TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1 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 "TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1" \
    --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": "TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1",
		"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 "TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1" \
        --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": "TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1 with Docker Model Runner:
```
docker model run hf.co/TroyDoesAI/Smaug-8-Layer-Chunk-Experiment1
```

DONT DOWNLOAD UNLESS YOUR WORKING ON MAKING EXPERTS FOR MOE THAT KNOW MERMAID DIAGRAMS, THIS IS MY FIRST EXPERT THAT KNOWS SYNTAX ONLY, IT WILL NOT BE USEFUL WITHOUT THE REST OF MY EXPERTS I AM CREATING.

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Safetensors

Model size

9B params

Tensor type

F16