Instructions to use Aryanne/Astrohermes-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aryanne/Astrohermes-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Aryanne/Astrohermes-3B", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Aryanne/Astrohermes-3B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Aryanne/Astrohermes-3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Aryanne/Astrohermes-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/Astrohermes-3B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Aryanne/Astrohermes-3B
- SGLang
How to use Aryanne/Astrohermes-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/Astrohermes-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/Astrohermes-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/Astrohermes-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/Astrohermes-3B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Aryanne/Astrohermes-3B with Docker Model Runner:
docker model run hf.co/Aryanne/Astrohermes-3B
metadata
language:
- en
library_name: transformers
tags:
- gpt
- llm
- stablelm
inference: true
license: cc-by-sa-4.0
This model is a mix of PAIXAI/Astrid-3B + jondurbin/airoboros-3b-3p0 + cxllin/StableHermes-3b, as shown in the yaml(see Astrohermes.yml or below). Aryanne/Astridboros-3B = PAIXAI/Astrid-3B + jondurbin/airoboros-3b-3p0
slices:
- sources:
- model: Aryanne/Astridboros-3B
layer_range: [0, 15]
- sources:
- model: cxllin/StableHermes-3b
layer_range: [15, 16]
- sources:
- model: Aryanne/Astridboros-3B
layer_range: [16, 17]
- sources:
- model: cxllin/StableHermes-3b
layer_range: [17, 18]
- sources:
- model: Aryanne/Astridboros-3B
layer_range: [18, 19]
- sources:
- model: cxllin/StableHermes-3b
layer_range: [19, 20]
- sources:
- model: Aryanne/Astridboros-3B
layer_range: [20, 21]
- sources:
- model: cxllin/StableHermes-3b
layer_range: [21, 22]
- sources:
- model: Aryanne/Astridboros-3B
layer_range: [22, 23]
- sources:
- model: cxllin/StableHermes-3b
layer_range: [23, 24]
- sources:
- model: Aryanne/Astridboros-3B
layer_range: [24, 32]
merge_method: passthrough
dtype: float16
I recommend the use of alpaca prompt format.
GGUF Quants: afrideva/Astrohermes-3B-GGUF