Instructions to use Aryanne/Astrorocketboros-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Aryanne/Astrorocketboros-3B with Transformers:

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

pipe = pipeline("text-generation", model="Aryanne/Astrorocketboros-3B", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Aryanne/Astrorocketboros-3B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Aryanne/Astrorocketboros-3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Aryanne/Astrorocketboros-3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Aryanne/Astrorocketboros-3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Aryanne/Astrorocketboros-3B

SGLang

How to use Aryanne/Astrorocketboros-3B 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 "Aryanne/Astrorocketboros-3B" \
    --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": "Aryanne/Astrorocketboros-3B",
		"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 "Aryanne/Astrorocketboros-3B" \
        --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": "Aryanne/Astrorocketboros-3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Aryanne/Astrorocketboros-3B with Docker Model Runner:
```
docker model run hf.co/Aryanne/Astrorocketboros-3B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

This model is a task_arithmetic merge of pansophic/rocket-3B, jondurbin/airoboros-3b-3p0 and Aryanne/Astrohermes-3B, as shown in the yaml(see Astrorocketboros.yml or below).

I used this model as base ayoubkirouane/StableLM-3B

I'm not sure if all the .json files are all right, but it seems to work at the moment.

merge_method: task_arithmetic
base_model: ayoubkirouane/StableLM-3B
models:
  - model: ayoubkirouane/StableLM-3B
  - model: pansophic/rocket-3B
    parameters:
      weight: 1.0
  - model: Aryanne/Astrohermes-3B
    parameters:
      weight: 0.22
  - model: jondurbin/airoboros-3b-3p0
    parameters:
      weight: 0.1
dtype: float16

I recommend the use of chatml prompt format, but alpaca seems to work too but it's necessary to write something before the instruction:

You are an Assistant
### Instruction:
write a poem.
### Response:
Amidst the tranquil hues of twilight's hue,
As shadows stretch and dance with whispered dew,
The trees weave tales of ages past untold,

GGUF Quants: afrideva/Astrorocketboros-3B-GGUF

Downloads last month: 36

Safetensors

Model size

3B params

Tensor type

F16

Model tree for Aryanne/Astrorocketboros-3B

Quantizations

1 model