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, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

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
```

Aryanne commited on Dec 7, 2023

Commit

403953e

1 Parent(s): 4e067cb

Create README.md

Browse files

Files changed (1) hide show

README.md +45 -0

README.md ADDED Viewed

	@@ -0,0 +1,45 @@

+---
+language:
+- en
+library_name: transformers
+tags:
+- gpt
+- llm
+- stablelm
+inference: true
+license: cc-by-sa-4.0
+---
+This model is a task_arithmetic merge of [pansophic/rocket-3B](https://huggingface.co/pansophic/rocket-3B), [jondurbin/airoboros-3b-3p0](https://huggingface.co/jondurbin/airoboros-3b-3p0) and [Aryanne/Astrohermes-3B](https://huggingface.co/Aryanne/Astrohermes-3B), as shown in the yaml(see Astrorocketboros.yml or below).
+I used this model as base [ayoubkirouane/StableLM-3B](https://huggingface.co/ayoubkirouane/StableLM-3B)
+I'm not sure if all the .json files are all right, but it seems to work at the moment.
+```yaml
+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: [notyet]()