Instructions to use yuchenxie/arlowgpt-dummy-weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use yuchenxie/arlowgpt-dummy-weights with Transformers:

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

pipe = pipeline("text-generation", model="yuchenxie/arlowgpt-dummy-weights")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("yuchenxie/arlowgpt-dummy-weights", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use yuchenxie/arlowgpt-dummy-weights with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/yuchenxie/arlowgpt-dummy-weights

SGLang

How to use yuchenxie/arlowgpt-dummy-weights 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 "yuchenxie/arlowgpt-dummy-weights" \
    --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": "yuchenxie/arlowgpt-dummy-weights",
		"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 "yuchenxie/arlowgpt-dummy-weights" \
        --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": "yuchenxie/arlowgpt-dummy-weights",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use yuchenxie/arlowgpt-dummy-weights with Docker Model Runner:
```
docker model run hf.co/yuchenxie/arlowgpt-dummy-weights
```

DUMMY WEIGHTS ONLY !! NOT REAL MODEL !!

Specifications (Will be carried out to the main fully released model)

Architecture: arlow (Not supported by transformers right now, but beta version is out -> here)

Exact location: here

Will feature:

GQA
Silu
Flash Attention VarLen + manual QKV proj
cross attention (untrained, there for easy vision encoder incorporation)
model is decoder only, however, cross attention weights is there.
Custom RoPE
and more!

Arlow architecture isn't officially supported by transformers but my implementation will be there if you want to try it.

Downloads last month: 23

Safetensors

Model size

0.4B params

Tensor type

BF16