Instructions to use AxeronAI/axeron-mf-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AxeronAI/axeron-mf-32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AxeronAI/axeron-mf-32")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AxeronAI/axeron-mf-32") model = AutoModelForCausalLM.from_pretrained("AxeronAI/axeron-mf-32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use AxeronAI/axeron-mf-32 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AxeronAI/axeron-mf-32" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AxeronAI/axeron-mf-32", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AxeronAI/axeron-mf-32
- SGLang
How to use AxeronAI/axeron-mf-32 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 "AxeronAI/axeron-mf-32" \ --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": "AxeronAI/axeron-mf-32", "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 "AxeronAI/axeron-mf-32" \ --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": "AxeronAI/axeron-mf-32", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AxeronAI/axeron-mf-32 with Docker Model Runner:
docker model run hf.co/AxeronAI/axeron-mf-32
axeron-32
This is a forge of pre-trained language models created using forgelm.
Forge Details
Forge Method
This model was forged using the SLERP forge method.
Models Forged
The following models were included in the forge:
Configuration
The following YAML configuration was used to produce this model:
base_model: meta-llama/Llama-3.1-8B
dtype: bfloat16
forge_method: slerp
modules:
default:
slices:
- sources:
- layer_range: [0, 32]
model: meta-llama/Llama-3.1-8B
- layer_range: [0, 32]
model: meta-llama/Llama-3.1-8B-Instruct
parameters:
t: 0.5
tokenizer:
source: base
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Base model
meta-llama/Llama-3.1-8B