Instructions to use MarinaraSpaghetti/NemoMix-Unleashed-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarinaraSpaghetti/NemoMix-Unleashed-12B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MarinaraSpaghetti/NemoMix-Unleashed-12B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("MarinaraSpaghetti/NemoMix-Unleashed-12B") model = AutoModelForCausalLM.from_pretrained("MarinaraSpaghetti/NemoMix-Unleashed-12B", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use MarinaraSpaghetti/NemoMix-Unleashed-12B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MarinaraSpaghetti/NemoMix-Unleashed-12B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MarinaraSpaghetti/NemoMix-Unleashed-12B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/MarinaraSpaghetti/NemoMix-Unleashed-12B
- SGLang
How to use MarinaraSpaghetti/NemoMix-Unleashed-12B 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 "MarinaraSpaghetti/NemoMix-Unleashed-12B" \ --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": "MarinaraSpaghetti/NemoMix-Unleashed-12B", "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 "MarinaraSpaghetti/NemoMix-Unleashed-12B" \ --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": "MarinaraSpaghetti/NemoMix-Unleashed-12B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use MarinaraSpaghetti/NemoMix-Unleashed-12B with Docker Model Runner:
docker model run hf.co/MarinaraSpaghetti/NemoMix-Unleashed-12B
File size: 745 Bytes
73378fd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | models:
- model: E:\mergekit\mistralaiMistral-Nemo-Instruct-2407
parameters:
weight: 0.1
density: 0.4
- model: E:\mergekit\nbeerbower_mistral-nemo-bophades-12B
parameters:
weight: 0.12
density: 0.5
- model: E:\mergekit\nbeerbower_mistral-nemo-gutenberg-12B
parameters:
weight: 0.2
density: 0.6
- model: E:\mergekit\Sao10K_MN-12B-Lyra-v1
parameters:
weight: 0.25
density: 0.7
- model: E:\mergekit\intervitens_mini-magnum-12b-v1.1
parameters:
weight: 0.33
density: 0.8
merge_method: della_linear
base_model: E:\mergekit\mistralaiMistral-Nemo-Base-2407
parameters:
epsilon: 0.05
lambda: 1
dtype: bfloat16
tokenizer_source: base |